diff --git a/.gitignore b/.gitignore
index 00f2d38..f833587 100644
--- a/.gitignore
+++ b/.gitignore
@@ -1,3 +1,24 @@
+# Python
 __pycache__/
-*.pyc
+*.py[cod]
+.pytest_cache/
 .venv/
+venv/
+
+# IDE / OS
+.idea/
+.vscode/
+.DS_Store
+Thumbs.db
+
+# Raw data and generated outputs
+data/raw/
+work/
+outputs/
+*.rscap
+*.dorec
+*.log
+
+# Large generated point clouds outside the archived reference result
+**/frames/
+**/frames_all/
diff --git a/CONSENSUS_SELECTION.md b/CONSENSUS_SELECTION.md
deleted file mode 100644
index eb46fba..0000000
--- a/CONSENSUS_SELECTION.md
+++ /dev/null
@@ -1,12 +0,0 @@
-# 最终推荐值补充说明
-
-两套后端各自结果均保留。最终推荐值又增加了一层不依赖外参X的交叉检查：只有同一运动对的Open3D B与small_gicp B相差不超过5 cm、0.5°时才进入最终求解；最终B数为39对。
-
-最终推荐：
-
-- 平移 `[1.297760, -0.000067, 0.720498] m`
-- RPY `[-0.785151, 1.202661, -0.835510] deg`
-- 第二批AX RMS：`0.07985 m / 0.96118°`
-- 第一批22对辅助复核：`0.06067 m / 1.00298°`
-
-完整结果见 `results/final_extrinsic_recommended.json`，选择摘要见 `results/final_summary.json`。执行完整 `run_all.ps1` 后，再执行 `run_consensus_finish.ps1` 可重建最终推荐结果。
diff --git a/LICENSE b/LICENSE
deleted file mode 100644
index f63f5a9..0000000
--- a/LICENSE
+++ /dev/null
@@ -1,194 +0,0 @@
-木兰宽松许可证，第2版
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-PSL v2.
-You may obtain a copy of Mulan PSL v2 at:
-         http://license.coscl.org.cn/MulanPSL2
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-Mulan Permissive Software License，Version 2 (Mulan PSL v2)
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diff --git a/LiDAR_RTK_Direct_Calibration/.gitignore b/LiDAR_RTK_Direct_Calibration/.gitignore
deleted file mode 100644
index f833587..0000000
--- a/LiDAR_RTK_Direct_Calibration/.gitignore
+++ /dev/null
@@ -1,24 +0,0 @@
-# Python
-__pycache__/
-*.py[cod]
-.pytest_cache/
-.venv/
-venv/
-
-# IDE / OS
-.idea/
-.vscode/
-.DS_Store
-Thumbs.db
-
-# Raw data and generated outputs
-data/raw/
-work/
-outputs/
-*.rscap
-*.dorec
-*.log
-
-# Large generated point clouds outside the archived reference result
-**/frames/
-**/frames_all/
diff --git a/LiDAR_RTK_Direct_Calibration/README.md b/LiDAR_RTK_Direct_Calibration/README.md
deleted file mode 100644
index 95ff8cf..0000000
--- a/LiDAR_RTK_Direct_Calibration/README.md
+++ /dev/null
@@ -1,185 +0,0 @@
-# 双天线RTK—3D LiDAR直接手眼标定
-
-本仓库从静态站点原始数据复现 `T_RTK_lidar`：把原始雷达坐标转换到RTK导航坐标系。它**不是** `base_link` 车体外参，也不会在求解阶段使用车体航向偏置或RTK到后轮轴的XY杆臂。
-
-## 1. 输出坐标约定
-
-统一约定 `T_A_B` 把B系点变换到A系：
-
-```text
-p_RTK = T_RTK_lidar · p_lidar
-```
-
-RTK导航系在本仓库中定义为：
-
-- 原点：GGA位置参考点（通常为ANT1相位中心，必须结合接收机配置确认）；
-- X轴：`rawHeading`所表示的双天线基线在水平面的投影；
-- Y轴：左；
-- Z轴：上；
-- ENU航向：`yaw = 90° - rawHeading`；
-- roll、pitch：当前轨迹中固定为0。
-
-如果下游需要 `T_body_lidar`，必须另有经过确认的 `T_body_rtk`：
-
-```text
-T_body_lidar = T_body_rtk · T_RTK_lidar
-```
-
-## 2. 算法流程
-
-```text
-逐站LiDAR dlog + RTK.rscap + IMU.rscap
-  → 分别解析并保留原始字段
-  → 以LiDAR帧时间为索引关联RTK/IMU，生成combined NPZ
-  → 每站选择一帧静态点云，GGA转局部ENU，rawHeading构造yaw-only RTK pose
-  → Open3D GICP和small_gicp分别求 B_ij = T_Li_Lj
-  → 留出点、Hessian、正反向、多初值和旋转共轭不变量筛选
-  → 两后端共同认可的边形成consensus B
-  → A_ij X = X B_ij + 地面法向/高度约束求 X = T_RTK_lidar
-  → bootstrap、双后端差异、逐对残差和3D可视化检查
-```
-
-代码实际使用：
-
-```text
-A_ij = inv(T_W_Ri) · T_W_Rj = T_Ri_Rj
-B_ij = T_Li_Lj              # 将站点j点云变换到站点i
-A_ij · X = X · B_ij
-X = T_RTK_lidar
-```
-
-## 3. 原始数据目录
-
-大体积数据不提交Git。`DataRoot`下每个站点必须是一个独立dlog目录，至少包含：
-
-```text
-raw_dataset/
-├── stations/
-│   ├── 001/
-│   │   ├── dobject/
-│   │   └── dobject_recording/
-│   ├── 002/
-│   └── ...
-└── captures/
-    ├── rtk.rscap
-    └── imu.rscap
-```
-
-每个站点应在车辆完全静止后记录点云；建议不少于30站，并包含充足的直行、左转、右转和大角度转向姿态变化。
-
-## 4. 环境安装
-
-已验证环境为Windows、PowerShell、Python 3.11。安装依赖：
-
-```powershell
-python -m pip install -r requirements.txt
-```
-
-依赖包括NumPy、SciPy、Open3D和small_gicp。若small_gicp没有对应Windows wheel，可在WSL2中安装后运行Python核心命令，或先只运行Open3D后端；完整共识流程需要两个后端都可用。
-
-## 5. 从原始数据一键复现
-
-在仓库根目录执行，路径由使用者通过参数传入，脚本内没有本机绝对路径：
-
-```powershell
-$Repo = (Resolve-Path ".").Path
-$Raw = "E:\calibration_data\data4"
-$Out = "E:\calibration_output\rtk_lidar"
-
-powershell.exe -NoProfile -ExecutionPolicy Bypass -File "$Repo\run\run_full_pipeline.ps1" `
-  -DataRoot "$Raw\stations" `
-  -RtkCapture "$Raw\captures\rtk.rscap" `
-  -ImuCapture "$Raw\captures\imu.rscap" `
-  -OutputRoot $Out `
-  -RtkReferenceHeightAboveGroundM 0.8535 `
-  -ExpectedStations 34
-```
-
-主要输出：
-
-```text
-$Out/
-├── exported/
-│   ├── export/          # 各站LiDAR逐帧NPZ
-│   ├── parsed/          # RTK/IMU JSONL
-│   └── combined/        # 按LiDAR帧关联后的多传感器NPZ
-├── prepared_rtk_direct/
-│   ├── frames_all/      # 每站选中的静态帧
-│   └── reference_poses_rtk_gga_raw_heading.csv
-└── calibration/
-    ├── open3d_gicp/
-    ├── small_gicp/
-    ├── consensus/
-    ├── summary.json
-    └── final_T_RTK_lidar.json
-```
-
-若已经有`combined/`，可跳过原始导出：
-
-```powershell
-powershell.exe -NoProfile -ExecutionPolicy Bypass -File "$Repo\run\run_direct_rtk_lidar.ps1" `
-  -CombinedRoot "E:\calibration_output\exported\combined" `
-  -WorkRoot "E:\calibration_output\prepared_rtk_direct" `
-  -OutputRoot "E:\calibration_output\calibration" `
-  -RtkReferenceHeightAboveGroundM 0.8535 `
-  -ExpectedStations 34
-```
-
-## 6. 3D可视化
-
-```powershell
-powershell.exe -NoProfile -ExecutionPolicy Bypass -File "$Repo\run\view_result.ps1" `
-  -Frames "$Out\prepared_rtk_direct\frames_all" `
-  -Pairs "$Out\calibration\consensus\B_consensus.npz" `
-  -Extrinsic "$Out\calibration\final_T_RTK_lidar.json" `
-  -PairIndex 0
-```
-
-窗口中：
-
-- 蓝色：目标站点i；橙色：站点j；
-- `1`：原始点云；
-- `2`：RTK运动A直接作为初值；
-- `3`：GICP测得的B；
-- `4`：最终外参预测的 `X^-1 A X`；
-- `Q/Esc`：退出。
-
-模式3和4应让同一墙面、立柱、路缘和地面尽量重合。终端同时打印 `B^-1(X^-1AX)` 的平移和旋转增量。应查看多对，不能只挑视觉效果最好的一对。
-
-## 7. data4参考结果
-
-仓库保留了精简参考产物，见[`results/reference_data4`](results/reference_data4/README.md)：
-
-```text
-translation_m = [1.638179350, -0.240844799, 0.084481236]
-RPY_deg_xyz   = [-0.817167459, 1.323288119, -22.104163318]
-
-站点：34
-共识运动对：25
-AX Translation RMS：0.100207 m
-AX Rotation RMS：1.252794°
-Weighted Jacobian condition：7.739413
-Open3D vs small_gicp：0.003889 m / 0.188431°
-```
-
-唯一建议下游读取的参考结果是[`final_T_RTK_lidar.json`](results/reference_data4/final_T_RTK_lidar.json)。
-
-## 8. z与精度限制
-
-平面阿克曼运动不能独立观测z。参考结果使用34站地面平面和RTK参考点离地`0.8535 m`约束z；该高度必须量到实际GGA参考点/天线相位中心。更改参考高度后必须重新求解。
-
-AX残差、Hessian/Jacobian条件数、bootstrap和双后端一致性只证明内部一致性，不能单独证明逐帧GT达到±3 cm。当前关联仍以LiDAR和串口主机接收时间为主；GNSS周/周内时间和IMU设备时间被保留，但没有联合估计时钟偏移与漂移。用于连续GT pose前，应补做严格设备时间同步和独立轨迹验证。
-
-此外，代码无法单独证明GGA对应哪根物理天线、`rawHeading`是ANT1→ANT2还是ANT2→ANT1；必须用接收机配置、接线和现场运动实验确认。方向错误会导致RTK坐标系yaw相差约180°。
-
-## 9. 仓库目录
-
-| 目录 | 职责 |
-|---|---|
-| [`code/`](code/) | GICP、运动对质量评价、AX=XB求解、结果封装和3D可视化 |
-| [`tools/`](tools/) | 原始dlog/rscap解析、按LiDAR帧关联及静态站点prepared生成 |
-| [`run/`](run/) | PowerShell入口；所有数据和输出路径都通过参数传入 |
-| [`results/reference_data4/`](results/reference_data4/) | 可提交Git的精简参考结果，不包含点云和本机过程目录 |
-| `work/`、`outputs/` | 本地运行生成物，已由`.gitignore`排除 |
-
-各代码文件职责见[`code/README.md`](code/README.md)，命令索引见[`run/README.md`](run/README.md)，工具说明见[`tools/README.md`](tools/README.md)。
diff --git a/LiDAR_RTK_Direct_Calibration/code/compare_extrinsics.py b/LiDAR_RTK_Direct_Calibration/code/compare_extrinsics.py
deleted file mode 100644
index b407738..0000000
--- a/LiDAR_RTK_Direct_Calibration/code/compare_extrinsics.py
+++ /dev/null
@@ -1,43 +0,0 @@
-#!/usr/bin/env python3
-"""Compare two homogeneous-extrinsic JSON files in parameter space and on SE(3)."""
-
-import argparse
-import json
-from pathlib import Path
-
-import numpy as np
-from scipy.spatial.transform import Rotation
-
-
-def main() -> int:
-    parser = argparse.ArgumentParser(description=__doc__)
-    parser.add_argument("--reference", type=Path, required=True)
-    parser.add_argument("--candidate", type=Path, required=True)
-    parser.add_argument("--output", type=Path, required=True)
-    args = parser.parse_args()
-    reference = json.loads(args.reference.read_text(encoding="utf-8-sig"))
-    candidate = json.loads(args.candidate.read_text(encoding="utf-8-sig"))
-    a = np.asarray(reference["matrix_4x4"], dtype=float)
-    b = np.asarray(candidate["matrix_4x4"], dtype=float)
-    delta = np.linalg.inv(a) @ b
-    result = {
-        "convention": "delta = inverse(reference) @ candidate",
-        "reference": str(args.reference.resolve()),
-        "candidate": str(args.candidate.resolve()),
-        "candidate_minus_reference_translation_xyz_m": (b[:3, 3] - a[:3, 3]).tolist(),
-        "candidate_minus_reference_rpy_xyz_deg": (
-            np.asarray(candidate["rotation_rpy_deg_xyz"], float)
-            - np.asarray(reference["rotation_rpy_deg_xyz"], float)
-        ).tolist(),
-        "relative_translation_norm_m": float(np.linalg.norm(delta[:3, 3])),
-        "relative_rotation_deg": float(np.degrees(Rotation.from_matrix(delta[:3, :3]).magnitude())),
-        "relative_matrix_4x4": delta.tolist(),
-    }
-    args.output.parent.mkdir(parents=True, exist_ok=True)
-    args.output.write_text(json.dumps(result, ensure_ascii=False, indent=2), encoding="utf-8")
-    print(json.dumps(result, ensure_ascii=False, indent=2))
-    return 0
-
-
-if __name__ == "__main__":
-    raise SystemExit(main())
diff --git a/LiDAR_RTK_Direct_Calibration/code/cross_backend_filter.py b/LiDAR_RTK_Direct_Calibration/code/cross_backend_filter.py
deleted file mode 100644
index 95436ad..0000000
--- a/LiDAR_RTK_Direct_Calibration/code/cross_backend_filter.py
+++ /dev/null
@@ -1,81 +0,0 @@
-#!/usr/bin/env python3
-"""Keep common A/B edges on which Open3D and small_gicp agree, without using X."""
-import argparse
-import json
-from pathlib import Path
-
-import numpy as np
-from scipy.spatial.transform import Rotation
-
-
-def key(meta):
-    return int(meta[0]), int(meta[1])
-
-
-def main():
-    parser = argparse.ArgumentParser(description=__doc__)
-    parser.add_argument("--open3d-pairs", required=True)
-    parser.add_argument("--small-pairs", required=True)
-    parser.add_argument("--output", required=True)
-    parser.add_argument("--audit")
-    parser.add_argument("--max-translation", type=float, default=0.05)
-    parser.add_argument("--max-rotation", type=float, default=0.50)
-    parser.add_argument("--min-pairs", type=int, default=25)
-    args = parser.parse_args()
-
-    with np.load(args.open3d_pairs, allow_pickle=False) as source:
-        open_a = np.asarray(source["A"], float)
-        open_b = np.asarray(source["B"], float)
-        open_meta = np.asarray(source["meta"], float)
-        station_times = np.asarray(source["station_times"])
-        rtk_dt = np.asarray(source["rtk_nearest_dt_s"])
-    with np.load(args.small_pairs, allow_pickle=False) as source:
-        small = {key(meta): np.asarray(b, float)
-                 for meta, b in zip(source["meta"], source["B"])}
-
-    keep, audit = [], []
-    for meta, b_open in zip(open_meta, open_b):
-        edge = key(meta)
-        if edge not in small:
-            audit.append({"i": edge[0], "j": edge[1], "accepted": False,
-                          "reason": "not_in_small_gicp_refined"})
-            keep.append(False)
-            continue
-        delta = np.linalg.inv(b_open) @ small[edge]
-        translation = float(np.linalg.norm(delta[:3, 3]))
-        rotation = float(np.rad2deg(Rotation.from_matrix(delta[:3, :3]).magnitude()))
-        accepted = translation <= args.max_translation and rotation <= args.max_rotation
-        keep.append(accepted)
-        audit.append({
-            "i": edge[0], "j": edge[1],
-            "open3d_small_translation_m": translation,
-            "open3d_small_rotation_deg": rotation,
-            "accepted": accepted,
-            "reason": "" if accepted else "backend_disagreement",
-        })
-    keep = np.asarray(keep, bool)
-    output = Path(args.output)
-    output.parent.mkdir(parents=True, exist_ok=True)
-    np.savez_compressed(
-        output, A=open_a[keep], B=open_b[keep], meta=open_meta[keep],
-        station_times=station_times, rtk_nearest_dt_s=rtk_dt,
-        backend=np.asarray("open3d_gicp_cross_backend_consensus"),
-    )
-    audit_path = Path(args.audit or output.with_suffix(".consensus.json"))
-    audit_path.write_text(json.dumps({
-        "selection_is_X_independent": True,
-        "B_source": "Open3D; small_gicp is used only as an agreement gate",
-        "max_translation_m": args.max_translation,
-        "max_rotation_deg": args.max_rotation,
-        "input_open3d_pairs": len(open_b),
-        "accepted_pairs": int(np.count_nonzero(keep)),
-        "pairs": audit,
-    }, ensure_ascii=False, indent=2), encoding="utf-8")
-    if np.count_nonzero(keep) < args.min_pairs:
-        raise RuntimeError(f"only {np.count_nonzero(keep)} consensus pairs")
-    print(json.dumps({"accepted_pairs": int(np.count_nonzero(keep)),
-                      "output": str(output.resolve()), "audit": str(audit_path.resolve())}, indent=2))
-
-
-if __name__ == "__main__":
-    main()
diff --git a/LiDAR_RTK_Direct_Calibration/code/refine_pairs.py b/LiDAR_RTK_Direct_Calibration/code/refine_pairs.py
deleted file mode 100644
index f460d36..0000000
--- a/LiDAR_RTK_Direct_Calibration/code/refine_pairs.py
+++ /dev/null
@@ -1,87 +0,0 @@
-#!/usr/bin/env python3
-"""X-independent second-stage filter for stationary A/B pairs."""
-import argparse
-import json
-from pathlib import Path
-
-import numpy as np
-
-from rigorous_calibration import read_pairs, rotation_angle_deg
-
-
-def main():
-    parser = argparse.ArgumentParser(description=__doc__)
-    parser.add_argument("--pairs", required=True)
-    parser.add_argument("--quality-json", required=True)
-    parser.add_argument("--output", required=True)
-    parser.add_argument("--audit")
-    parser.add_argument("--min-pairs", type=int, default=25)
-    parser.add_argument("--min-inlier-ratio", type=float, default=0.70)
-    parser.add_argument("--max-inlier-rmse", type=float, default=0.13)
-    parser.add_argument("--max-rotation-invariant-error", type=float, default=0.75)
-    parser.add_argument("--reverse-translation-tolerance", type=float, default=0.05)
-    parser.add_argument("--reverse-rotation-tolerance", type=float, default=0.50)
-    args = parser.parse_args()
-
-    a_array, b_array, meta, _ = read_pairs(args.pairs)
-    quality = json.loads(Path(args.quality_json).read_text(encoding="utf-8-sig"))
-    reports = {(int(item["i"]), int(item["j"])): item for item in quality["pairs"]}
-    keep, audit = [], []
-    for a_ij, b_ij, item_meta in zip(a_array, b_array, meta):
-        key = (int(item_meta[0]), int(item_meta[1]))
-        report = reports[key]
-        heldout = report["heldout_symmetric"]
-        reverse = report["forward_reverse"]
-        invariant = abs(rotation_angle_deg(a_ij[:3, :3]) - rotation_angle_deg(b_ij[:3, :3]))
-        reasons = []
-        if heldout["inlier_ratio"] < args.min_inlier_ratio:
-            reasons.append("overlap_ratio")
-        if heldout["inlier_rmse_m"] is None or heldout["inlier_rmse_m"] > args.max_inlier_rmse:
-            reasons.append("heldout_rmse")
-        if invariant > args.max_rotation_invariant_error:
-            reasons.append("rotation_conjugacy_invariant")
-        if reverse["translation_m"] > args.reverse_translation_tolerance:
-            reasons.append("forward_reverse_translation")
-        if reverse["rotation_deg"] > args.reverse_rotation_tolerance:
-            reasons.append("forward_reverse_rotation")
-        accepted = not reasons
-        keep.append(accepted)
-        audit.append({
-            "i": key[0], "j": key[1], "heldout_inlier_ratio": heldout["inlier_ratio"],
-            "heldout_inlier_rmse_m": heldout["inlier_rmse_m"],
-            "rotation_invariant_error_deg": invariant,
-            "reverse_translation_m": reverse["translation_m"],
-            "reverse_rotation_deg": reverse["rotation_deg"],
-            "accepted": accepted, "rejection_reasons": reasons,
-        })
-    keep = np.asarray(keep, bool)
-    output = Path(args.output)
-    output.parent.mkdir(parents=True, exist_ok=True)
-    with np.load(args.pairs, allow_pickle=False) as source:
-        np.savez_compressed(
-            output, A=a_array[keep], B=b_array[keep], meta=meta[keep],
-            station_times=np.asarray(source["station_times"]),
-            rtk_nearest_dt_s=np.asarray(source["rtk_nearest_dt_s"]),
-            backend=np.asarray(source["backend"]),
-        )
-    audit_path = Path(args.audit or output.with_suffix(".refinement.json"))
-    audit_path.write_text(json.dumps({
-        "selection_is_X_independent": True,
-        "criteria": {
-            "min_inlier_ratio": args.min_inlier_ratio,
-            "max_inlier_rmse_m": args.max_inlier_rmse,
-            "max_rotation_invariant_error_deg": args.max_rotation_invariant_error,
-            "reverse_translation_tolerance_m": args.reverse_translation_tolerance,
-            "reverse_rotation_tolerance_deg": args.reverse_rotation_tolerance,
-        },
-        "input_pairs": len(keep), "accepted_pairs": int(np.count_nonzero(keep)),
-        "pairs": audit,
-    }, ensure_ascii=False, indent=2), encoding="utf-8")
-    if np.count_nonzero(keep) < args.min_pairs:
-        raise RuntimeError(f"only {np.count_nonzero(keep)} refined pairs; need {args.min_pairs}")
-    print(json.dumps({"input_pairs": len(keep), "accepted_pairs": int(np.count_nonzero(keep)),
-                      "output": str(output.resolve()), "audit": str(audit_path.resolve())}, indent=2))
-
-
-if __name__ == "__main__":
-    main()
diff --git a/LiDAR_RTK_Direct_Calibration/code/rigorous_calibration.py b/LiDAR_RTK_Direct_Calibration/code/rigorous_calibration.py
deleted file mode 100644
index 0974795..0000000
--- a/LiDAR_RTK_Direct_Calibration/code/rigorous_calibration.py
+++ /dev/null
@@ -1,771 +0,0 @@
-#!/usr/bin/env python3
-"""Rigorous stationary LiDAR / reference-trajectory hand-eye calibration.
-
-Convention: T_A_B maps points from frame B into frame A.
-For this repository the reference frame is the RTK navigation frame.
-X = T_RTK_lidar, A_ij = T_W_Ri^-1 T_W_Rj, B_ij = T_Li_Lj,
-therefore A_ij X = X B_ij. Raw sensor-frame points_raw are used.
-"""
-from __future__ import annotations
-
-import argparse
-import csv
-import json
-import math
-import time
-from dataclasses import dataclass
-from pathlib import Path
-
-import numpy as np
-from scipy.optimize import least_squares
-from scipy.spatial import cKDTree
-
-
-def skew(v):
-    x, y, z = v
-    return np.array([[0.0, -z, y], [z, 0.0, -x], [-y, x, 0.0]])
-
-
-def so3_exp(v):
-    angle = float(np.linalg.norm(v))
-    if angle < 1e-12:
-        return np.eye(3) + skew(v)
-    k = skew(np.asarray(v, float) / angle)
-    return np.eye(3) + math.sin(angle) * k + (1.0 - math.cos(angle)) * k @ k
-
-
-def so3_log(rotation):
-    cosine = float(np.clip((np.trace(rotation) - 1.0) / 2.0, -1.0, 1.0))
-    angle = math.acos(cosine)
-    vee = np.array([
-        rotation[2, 1] - rotation[1, 2],
-        rotation[0, 2] - rotation[2, 0],
-        rotation[1, 0] - rotation[0, 1],
-    ])
-    if angle < 1e-9:
-        return vee / 2.0
-    if abs(math.pi - angle) < 1e-5:
-        values, vectors = np.linalg.eigh((rotation + np.eye(3)) / 2.0)
-        return vectors[:, int(np.argmax(values))] * angle
-    return vee * angle / (2.0 * math.sin(angle))
-
-
-def quat_to_rotation(q):
-    x, y, z, w = np.asarray(q, float) / np.linalg.norm(q)
-    return np.array([
-        [1-2*(y*y+z*z), 2*(x*y-z*w), 2*(x*z+y*w)],
-        [2*(x*y+z*w), 1-2*(x*x+z*z), 2*(y*z-x*w)],
-        [2*(x*z-y*w), 2*(y*z+x*w), 1-2*(x*x+y*y)],
-    ])
-
-
-def rotation_to_quat(rotation):
-    from scipy.spatial.transform import Rotation
-    return Rotation.from_matrix(rotation).as_quat()
-
-
-def rpy_deg(rotation):
-    from scipy.spatial.transform import Rotation
-    return Rotation.from_matrix(rotation).as_euler("xyz", degrees=True).tolist()
-
-
-def make_transform(translation, rotation):
-    transform = np.eye(4)
-    transform[:3, :3] = rotation
-    transform[:3, 3] = translation
-    return transform
-
-
-def params_transform(params):
-    return make_transform(params[:3], so3_exp(params[3:]))
-
-
-def inverse_transform(transform):
-    answer = np.eye(4)
-    answer[:3, :3] = transform[:3, :3].T
-    answer[:3, 3] = -answer[:3, :3] @ transform[:3, 3]
-    return answer
-
-
-def transform_points(points, transform):
-    return points @ transform[:3, :3].T + transform[:3, 3]
-
-
-def rotation_angle_deg(rotation):
-    return math.degrees(np.linalg.norm(so3_log(rotation)))
-
-
-@dataclass
-class PoseSeries:
-    time: np.ndarray
-    transforms: np.ndarray
-
-
-def read_poses(path):
-    timestamps, transforms = [], []
-    with Path(path).open(encoding="utf-8-sig", newline="") as stream:
-        reader = csv.DictReader(stream)
-        required = ("time", "x", "y", "z", "qx", "qy", "qz", "qw")
-        missing = [key for key in required if key not in (reader.fieldnames or [])]
-        if missing:
-            raise ValueError(f"{path}: missing pose fields {missing}")
-        for row in reader:
-            timestamps.append(float(row["time"]))
-            translation = np.array([float(row[k]) for k in ("x", "y", "z")])
-            quaternion = np.array([float(row[k]) for k in ("qx", "qy", "qz", "qw")])
-            transforms.append(make_transform(translation, quat_to_rotation(quaternion)))
-    order = np.argsort(timestamps)
-    return PoseSeries(np.asarray(timestamps)[order], np.asarray(transforms)[order])
-
-
-def nearest_pose(series, timestamp):
-    index = int(np.argmin(np.abs(series.time - timestamp)))
-    return series.transforms[index], float(abs(series.time[index] - timestamp))
-
-
-def npz_files(root):
-    files = sorted(Path(root).rglob("*.npz"))
-    if not files:
-        raise FileNotFoundError(f"no NPZ files under {root}")
-    return files
-
-
-def load_npz_xyz(path, min_range=1.0, max_range=50.0):
-    with np.load(path, allow_pickle=False) as data:
-        if "points_raw" not in data:
-            raise ValueError(f"{path}: points_raw is required; cart-frame points are forbidden")
-        raw = np.asarray(data["points_raw"], dtype=np.float64)
-        timestamp = float(np.ravel(data["unix_time_ns"])[0]) / 1e9
-        counter = int(np.ravel(data["frame_counter"])[0])
-    distance = raw[:, 0] * 0.001
-    azimuth = np.deg2rad(raw[:, 1])
-    altitude = np.deg2rad(raw[:, 2])
-    valid = (
-        np.isfinite(distance + azimuth + altitude)
-        & (distance >= min_range)
-        & (distance <= max_range)
-    )
-    distance, azimuth, altitude = distance[valid], azimuth[valid], altitude[valid]
-    xyz = np.column_stack((
-        distance * np.cos(altitude) * np.cos(azimuth),
-        distance * np.cos(altitude) * np.sin(azimuth),
-        distance * np.sin(altitude),
-    ))
-    return timestamp, counter, xyz
-
-
-def load_stations(root, min_range, max_range, z_min=None, z_max=None):
-    stations = []
-    for path in npz_files(root):
-        timestamp, counter, xyz = load_npz_xyz(path, min_range, max_range)
-        if z_min is not None:
-            xyz = xyz[(xyz[:, 2] >= z_min) & (xyz[:, 2] <= z_max)]
-        stations.append((timestamp, counter, path, xyz))
-    stations.sort(key=lambda item: item[0])
-    return stations
-
-
-def split_holdout(points, fraction, phase):
-    stride = max(int(round(1.0 / fraction)), 2)
-    index = np.arange(len(points))
-    holdout = ((index + phase) % stride) == 0
-    return points[~holdout], points[holdout]
-
-
-def make_o3d_cloud(points, voxel):
-    import open3d as o3d
-    cloud = o3d.geometry.PointCloud()
-    cloud.points = o3d.utility.Vector3dVector(np.asarray(points, float))
-    return cloud.voxel_down_sample(voxel)
-
-
-def align_open3d(target, source, initial, voxels, correspondences, iterations):
-    import open3d as o3d
-    registration = o3d.pipelines.registration
-    estimate = registration.TransformationEstimationForGeneralizedICP()
-    criteria = registration.ICPConvergenceCriteria(max_iteration=iterations)
-    transform, stages = np.asarray(initial, float), []
-    final_target = final_source = final_answer = None
-    started = time.perf_counter()
-    for voxel, correspondence in zip(voxels, correspondences):
-        target_cloud = make_o3d_cloud(target, voxel)
-        source_cloud = make_o3d_cloud(source, voxel)
-        answer = registration.registration_generalized_icp(
-            source_cloud, target_cloud, correspondence, transform, estimate, criteria
-        )
-        transform = np.asarray(answer.transformation, float)
-        stages.append({
-            "voxel_m": voxel,
-            "max_correspondence_m": correspondence,
-            "fitness": float(answer.fitness),
-            "inlier_rmse_m": float(answer.inlier_rmse),
-            "target_points": len(target_cloud.points),
-            "source_points": len(source_cloud.points),
-        })
-        final_target, final_source, final_answer = target_cloud, source_cloud, answer
-    information = registration.get_information_matrix_from_point_clouds(
-        final_source, final_target, correspondences[-1], transform
-    )
-    inliers = int(round(float(final_answer.fitness) * len(final_source.points)))
-    return {
-        "transform": transform,
-        "hessian": np.asarray(information, float),
-        "converged": None,
-        "iterations": None,
-        "num_inliers": inliers,
-        "objective": float(final_answer.inlier_rmse ** 2 * max(inliers, 1)),
-        "elapsed_sec": time.perf_counter() - started,
-        "stages": stages,
-    }
-
-
-def align_small_gicp(target, source, initial, voxels, correspondences, iterations, threads):
-    import small_gicp
-    transform, stages, result = np.asarray(initial, float), [], None
-    started = time.perf_counter()
-    for voxel, correspondence in zip(voxels, correspondences):
-        result = small_gicp.align(
-            np.ascontiguousarray(target),
-            np.ascontiguousarray(source),
-            transform,
-            registration_type="GICP",
-            downsampling_resolution=voxel,
-            max_correspondence_distance=correspondence,
-            num_threads=threads,
-            max_iterations=iterations,
-            rotation_epsilon=math.radians(0.005),
-            translation_epsilon=0.0005,
-            verbose=False,
-        )
-        transform = np.asarray(result.T_target_source, float)
-        stages.append({
-            "voxel_m": voxel,
-            "max_correspondence_m": correspondence,
-            "converged": bool(result.converged),
-            "iterations": int(result.iterations),
-            "num_inliers": int(result.num_inliers),
-            "objective": float(result.error),
-        })
-    return {
-        "transform": transform,
-        "hessian": np.asarray(result.H, float),
-        "converged": bool(result.converged),
-        "iterations": int(result.iterations),
-        "num_inliers": int(result.num_inliers),
-        "objective": float(result.error),
-        "elapsed_sec": time.perf_counter() - started,
-        "stages": stages,
-    }
-
-
-def align_backend(backend, target, source, initial, args):
-    if backend == "open3d":
-        return align_open3d(
-            target, source, initial, args.voxels, args.correspondences, args.iterations
-        )
-    return align_small_gicp(
-        target, source, initial, args.voxels, args.correspondences,
-        args.iterations, args.threads
-    )
-
-
-def symmetric_heldout_metrics(target_fit, target_holdout, source_fit, source_holdout,
-                              transform, threshold):
-    transformed_source_fit = transform_points(source_fit, transform)
-    transformed_source_holdout = transform_points(source_holdout, transform)
-    forward = cKDTree(target_fit).query(transformed_source_holdout, workers=-1)[0]
-    reverse = cKDTree(transformed_source_fit).query(target_holdout, workers=-1)[0]
-    distances = np.concatenate((forward, reverse))
-    inliers = distances[distances <= threshold]
-    return {
-        "evaluated": int(len(distances)),
-        "inliers": int(len(inliers)),
-        "inlier_ratio": float(len(inliers) / max(len(distances), 1)),
-        "inlier_rmse_m": float(np.sqrt(np.mean(inliers**2))) if len(inliers) else None,
-        "median_m": float(np.median(distances)),
-        "p90_m": float(np.quantile(distances, 0.90)),
-        "p95_m": float(np.quantile(distances, 0.95)),
-    }
-
-
-def hessian_metrics(hessian, characteristic_length=10.0):
-    hessian = 0.5 * (np.asarray(hessian, float) + np.asarray(hessian, float).T)
-    scale = np.diag([1.0 / characteristic_length] * 3 + [1.0] * 3)
-    scaled = scale.T @ hessian @ scale
-    values, vectors = np.linalg.eigh(scaled)
-    largest = max(float(np.max(np.abs(values))), np.finfo(float).eps)
-    positive = values[values > largest * 1e-9]
-    condition = float(positive[-1] / positive[0]) if len(positive) else float("inf")
-    return {
-        "native_order": ["rx_rad", "ry_rad", "rz_rad", "tx_m", "ty_m", "tz_m"],
-        "scaled_eigenvalues": values.tolist(),
-        "effective_rank": int(len(positive)),
-        "scaled_condition_number": condition,
-        "weakest_scaled_direction": vectors[:, int(np.argmin(values))].tolist(),
-    }
-
-
-def transform_difference(reference, candidate):
-    delta = inverse_transform(reference) @ candidate
-    return {
-        "translation_m": float(np.linalg.norm(delta[:3, 3])),
-        "rotation_deg": rotation_angle_deg(delta[:3, :3]),
-    }
-
-
-def loop_metrics(transforms):
-    loops = []
-    for (i, j), b_ij in transforms.items():
-        for (j2, k), b_jk in transforms.items():
-            if j2 != j or (i, k) not in transforms:
-                continue
-            loops.append(transform_difference(transforms[(i, k)], b_ij @ b_jk))
-    if not loops:
-        return {"count": 0}
-    translation = np.array([item["translation_m"] for item in loops])
-    rotation = np.array([item["rotation_deg"] for item in loops])
-    return {
-        "count": len(loops),
-        "translation_rms_m": float(np.sqrt(np.mean(translation**2))),
-        "translation_p95_m": float(np.quantile(translation, 0.95)),
-        "rotation_rms_deg": float(np.sqrt(np.mean(rotation**2))),
-        "rotation_p95_deg": float(np.quantile(rotation, 0.95)),
-    }
-
-
-def cmd_ground(args):
-    stations = load_stations(args.frames, args.min_range, args.max_range)
-    rows = []
-    for timestamp, counter, _, xyz in stations:
-        roi = xyz[(xyz[:, 2] >= args.z_min) & (xyz[:, 2] <= args.z_max)]
-        if len(roi) < args.min_inliers:
-            continue
-        cloud = make_o3d_cloud(roi, args.voxel)
-        plane, indexes = cloud.segment_plane(
-            args.distance_threshold, 3, args.ransac_iterations
-        )
-        normal = np.asarray(plane[:3], float)
-        norm = np.linalg.norm(normal)
-        normal, distance = normal / norm, float(plane[3] / norm)
-        if distance < 0:
-            normal, distance = -normal, -distance
-        points = np.asarray(cloud.points)[indexes]
-        rms = float(np.sqrt(np.mean((points @ normal + distance) ** 2)))
-        if len(indexes) >= args.min_inliers and rms <= args.max_rms:
-            rows.append([timestamp, *normal, distance, len(indexes), rms, counter])
-    output = Path(args.output)
-    output.parent.mkdir(parents=True, exist_ok=True)
-    with output.open("w", encoding="utf-8", newline="") as stream:
-        writer = csv.writer(stream)
-        writer.writerow(["time", "nx", "ny", "nz", "d", "inliers", "rms_m", "frame_counter"])
-        writer.writerows(rows)
-    print(json.dumps({"planes": len(rows), "output": str(output.resolve())}, indent=2))
-
-
-def cmd_pairs(args):
-    if len(args.voxels) != len(args.correspondences):
-        raise ValueError("--voxels and --correspondences must have equal lengths")
-    stations = load_stations(
-        args.frames, args.min_range, args.max_range, args.z_min, args.z_max
-    )
-    reference = read_poses(args.reference_poses)
-    if len(stations) < args.min_stations:
-        raise ValueError(f"need at least {args.min_stations} stations, got {len(stations)}")
-    reference_poses, reference_dt = [], []
-    for timestamp, _, _, xyz in stations:
-        if len(xyz) < args.min_roi_points:
-            raise ValueError(f"station at {timestamp} has only {len(xyz)} ROI points")
-        pose, dt = nearest_pose(reference, timestamp + args.time_offset)
-        reference_poses.append(pose)
-        reference_dt.append(dt)
-    reference_poses = np.asarray(reference_poses)
-    split = [split_holdout(station[3], args.holdout_fraction, i)
-             for i, station in enumerate(stations)]
-    rng = np.random.default_rng(args.seed)
-    accepted_a, accepted_b, accepted_meta, reports = [], [], [], []
-    accepted_transforms = {}
-    for i in range(len(stations)):
-        for j in range(i + args.min_gap, min(len(stations), i + args.max_gap + 1)):
-            a_ij = inverse_transform(reference_poses[i]) @ reference_poses[j]
-            translation = float(np.linalg.norm(a_ij[:2, 3]))
-            rotation = rotation_angle_deg(a_ij[:3, :3])
-            if translation < args.min_translation and rotation < args.min_rotation:
-                continue
-            initial_b = a_ij.copy()  # X0=I; no measured extrinsic.
-            target_fit, target_holdout = split[i]
-            source_fit, source_holdout = split[j]
-            forward = align_backend(args.backend, target_fit, source_fit, initial_b, args)
-            heldout = symmetric_heldout_metrics(
-                target_fit, target_holdout, source_fit, source_holdout,
-                forward["transform"], args.evaluation_distance
-            )
-            hessian = hessian_metrics(forward["hessian"])
-            reverse_answer = align_backend(
-                args.backend, source_fit, target_fit, inverse_transform(initial_b), args
-            )
-            reverse = transform_difference(
-                forward["transform"], inverse_transform(reverse_answer["transform"])
-            )
-            multistart = []
-            for _ in range(args.multistart):
-                perturb = np.r_[
-                    rng.normal(0.0, args.multistart_translation_sigma, 3),
-                    np.deg2rad(rng.normal(0.0, args.multistart_rotation_sigma, 3)),
-                ]
-                candidate = align_backend(
-                    args.backend, target_fit, source_fit,
-                    params_transform(perturb) @ initial_b, args
-                )
-                multistart.append(transform_difference(forward["transform"], candidate["transform"]))
-            stable = [
-                item["translation_m"] <= args.multistart_translation_tolerance
-                and item["rotation_deg"] <= args.multistart_rotation_tolerance
-                for item in multistart
-            ]
-            success_rate = float(np.mean(stable)) if stable else 1.0
-            reasons = []
-            if forward["converged"] is False:
-                reasons.append("backend_not_converged")
-            if heldout["inlier_ratio"] < args.min_inlier_ratio:
-                reasons.append("heldout_inlier_ratio")
-            if heldout["inlier_rmse_m"] is None or heldout["inlier_rmse_m"] > args.max_inlier_rmse:
-                reasons.append("heldout_inlier_rmse")
-            if hessian["effective_rank"] < 6:
-                reasons.append("hessian_rank")
-            if hessian["scaled_condition_number"] > args.max_hessian_condition:
-                reasons.append("hessian_condition")
-            if reverse["translation_m"] > args.reverse_translation_tolerance:
-                reasons.append("forward_reverse_translation")
-            if reverse["rotation_deg"] > args.reverse_rotation_tolerance:
-                reasons.append("forward_reverse_rotation")
-            if success_rate < args.min_multistart_success:
-                reasons.append("multistart_instability")
-            accepted = not reasons
-            report = {
-                "i": i, "j": j,
-                "lidar_time_i": stations[i][0], "lidar_time_j": stations[j][0],
-                "frame_counter_i": stations[i][1], "frame_counter_j": stations[j][1],
-                "rtk_translation_m": translation, "rtk_rotation_deg": rotation,
-                "nearest_rtk_dt_i_s": reference_dt[i], "nearest_rtk_dt_j_s": reference_dt[j],
-                "initial_B_source": "X0=identity; B0=A (no measured extrinsic)",
-                "B_ij_4x4": forward["transform"].tolist(),
-                "backend": args.backend, "backend_converged": forward["converged"],
-                "backend_iterations": forward["iterations"],
-                "backend_num_inliers": forward["num_inliers"],
-                "backend_objective": forward["objective"],
-                "backend_elapsed_sec": forward["elapsed_sec"],
-                "multiscale_stages": forward["stages"],
-                "heldout_symmetric": heldout, "hessian": hessian,
-                "forward_reverse": reverse,
-                "multistart": {"runs": len(multistart), "success_rate": success_rate,
-                               "deltas": multistart},
-                "accepted": accepted, "rejection_reasons": reasons,
-            }
-            reports.append(report)
-            print(f"{args.backend} {i:02d}->{j:02d} rmse={heldout['inlier_rmse_m']} "
-                  f"ratio={heldout['inlier_ratio']:.3f} accepted={accepted}")
-            if accepted:
-                accepted_a.append(a_ij)
-                accepted_b.append(forward["transform"])
-                accepted_meta.append([i, j, stations[i][0], stations[j][0]])
-                accepted_transforms[(i, j)] = forward["transform"]
-    output = Path(args.output)
-    output.parent.mkdir(parents=True, exist_ok=True)
-    np.savez_compressed(
-        output, A=np.asarray(accepted_a), B=np.asarray(accepted_b),
-        meta=np.asarray(accepted_meta),
-        station_times=np.asarray([item[0] for item in stations]),
-        rtk_nearest_dt_s=np.asarray(reference_dt), backend=np.asarray(args.backend),
-    )
-    quality = {
-        "schema_version": 2,
-        "backend": args.backend,
-        "transform_convention": "B_ij=T_Li_Lj maps station j points into station i",
-        "raw_point_field": "points_raw",
-        "measured_extrinsic_used_as_initial": False,
-        "stations": len(stations), "candidate_pairs": len(reports),
-        "accepted_pairs": len(accepted_a),
-        "parameters": vars(args),
-        "accepted_loop_closure": loop_metrics(accepted_transforms),
-        "pairs": reports,
-    }
-    quality["parameters"].pop("func", None)
-    quality_path = Path(args.quality_json or output.with_suffix(".quality.json"))
-    quality_path.write_text(json.dumps(quality, ensure_ascii=False, indent=2), encoding="utf-8")
-    csv_path = Path(args.quality_csv or output.with_suffix(".quality.csv"))
-    with csv_path.open("w", encoding="utf-8", newline="") as stream:
-        fields = ["i", "j", "rtk_translation_m", "rtk_rotation_deg",
-                  "heldout_inlier_ratio", "heldout_inlier_rmse_m",
-                  "hessian_rank", "hessian_condition", "reverse_translation_m",
-                  "reverse_rotation_deg", "multistart_success_rate", "accepted",
-                  "rejection_reasons"]
-        writer = csv.DictWriter(stream, fieldnames=fields)
-        writer.writeheader()
-        for item in reports:
-            writer.writerow({
-                "i": item["i"], "j": item["j"],
-                "rtk_translation_m": item["rtk_translation_m"],
-                "rtk_rotation_deg": item["rtk_rotation_deg"],
-                "heldout_inlier_ratio": item["heldout_symmetric"]["inlier_ratio"],
-                "heldout_inlier_rmse_m": item["heldout_symmetric"]["inlier_rmse_m"],
-                "hessian_rank": item["hessian"]["effective_rank"],
-                "hessian_condition": item["hessian"]["scaled_condition_number"],
-                "reverse_translation_m": item["forward_reverse"]["translation_m"],
-                "reverse_rotation_deg": item["forward_reverse"]["rotation_deg"],
-                "multistart_success_rate": item["multistart"]["success_rate"],
-                "accepted": item["accepted"],
-                "rejection_reasons": ";".join(item["rejection_reasons"]),
-            })
-    if len(accepted_a) < args.min_pairs:
-        raise RuntimeError(f"only {len(accepted_a)} accepted pairs; need {args.min_pairs}")
-    print(json.dumps({
-        "backend": args.backend, "stations": len(stations),
-        "candidate_pairs": len(reports), "accepted_pairs": len(accepted_a),
-        "output": str(output.resolve()), "quality_json": str(quality_path.resolve()),
-        "loop": quality["accepted_loop_closure"],
-    }, indent=2))
-
-
-def read_planes(path):
-    planes = []
-    with Path(path).open(encoding="utf-8-sig", newline="") as stream:
-        for row in csv.DictReader(stream):
-            normal = np.array([float(row[k]) for k in ("nx", "ny", "nz")])
-            norm = np.linalg.norm(normal)
-            normal, distance = normal / norm, float(row["d"]) / norm
-            if distance < 0:
-                normal, distance = -normal, -distance
-            planes.append([*normal, distance])
-    return np.asarray(planes)
-
-
-def read_pairs(path):
-    with np.load(path, allow_pickle=False) as data:
-        return (np.asarray(data["A"], float), np.asarray(data["B"], float),
-                np.asarray(data["meta"], float), len(data["station_times"]))
-
-
-def calibration_residual(params, a_array, b_array, planes, args):
-    x = params_transform(params)
-    values = []
-    for a_ij, b_ij in zip(a_array, b_array):
-        error = inverse_transform(a_ij @ x) @ x @ b_ij
-        values.extend((error[:3, 3] / args.translation_sigma).tolist())
-        values.extend((so3_log(error[:3, :3]) / math.radians(args.rotation_sigma)).tolist())
-    body_up = np.array([0.0, 0.0, 1.0])
-    for plane in planes:
-        normal_body = x[:3, :3] @ plane[:3]
-        values.extend((np.cross(normal_body, body_up) / args.plane_normal_sigma).tolist())
-        body_distance = plane[3] - float(normal_body @ x[:3, 3])
-        values.append((body_distance - args.reference_height) / args.plane_height_sigma)
-    return np.asarray(values)
-
-
-def pair_metrics(a_array, b_array, x):
-    translation, rotation, rows = [], [], []
-    for index, (a_ij, b_ij) in enumerate(zip(a_array, b_array)):
-        predicted = inverse_transform(x) @ a_ij @ x
-        delta = inverse_transform(b_ij) @ predicted
-        t = float(np.linalg.norm(delta[:3, 3]))
-        r = rotation_angle_deg(delta[:3, :3])
-        translation.append(t); rotation.append(r)
-        rows.append({"pair_index": index, "translation_m": t, "rotation_deg": r})
-    translation, rotation = np.asarray(translation), np.asarray(rotation)
-    def stats(values):
-        return {
-            "rms": float(np.sqrt(np.mean(values**2))),
-            "median": float(np.median(values)),
-            "p90": float(np.quantile(values, 0.90)),
-            "p95": float(np.quantile(values, 0.95)),
-            "max": float(np.max(values)),
-        }
-    return {"pairs": len(rows), "translation_m": stats(translation),
-            "rotation_deg": stats(rotation), "per_pair": rows}
-
-
-def solve_extrinsic(a_array, b_array, planes, args):
-    rng = np.random.default_rng(args.seed)
-    starts = [np.zeros(6)]
-    for _ in range(args.solver_multistart - 1):
-        starts.append(np.r_[
-            rng.normal(0.0, args.start_translation_sigma, 3),
-            np.deg2rad(rng.normal(0.0, args.start_rotation_sigma, 3)),
-        ])
-    candidates = []
-    lower = np.r_[[-5.0] * 3, [-math.pi] * 3]
-    upper = np.r_[[5.0] * 3, [math.pi] * 3]
-    for start in starts:
-        answer = least_squares(
-            calibration_residual, np.clip(start, lower, upper),
-            args=(a_array, b_array, planes, args),
-            bounds=(lower, upper), loss="huber", f_scale=1.5,
-            x_scale="jac", max_nfev=args.max_nfev,
-        )
-        candidates.append(answer)
-    best = min(candidates, key=lambda item: item.cost)
-    return best, candidates
-
-
-def cmd_calibrate(args):
-    a_array, b_array, meta, stations = read_pairs(args.pairs)
-    planes = read_planes(args.ground_planes)
-    best, candidates = solve_extrinsic(a_array, b_array, planes, args)
-    x = params_transform(best.x)
-    residual = calibration_residual(best.x, a_array, b_array, planes, args)
-    absolute = np.abs(residual)
-    weights = np.ones_like(residual)
-    weights[absolute > 1.5] = 1.5 / absolute[absolute > 1.5]
-    weighted_jacobian = best.jac * np.sqrt(weights)[:, None]
-    singular = np.linalg.svd(weighted_jacobian, compute_uv=False)
-    condition = float(singular[0] / max(singular[-1], 1e-15))
-    dof = max(len(residual) - 6, 1)
-    covariance = np.linalg.pinv(weighted_jacobian.T @ weighted_jacobian) * float(
-        np.sum(weights * residual**2) / dof
-    )
-    sigma = np.sqrt(np.maximum(np.diag(covariance), 0.0))
-    candidate_summary = []
-    for item in candidates:
-        candidate_x = params_transform(item.x)
-        candidate_summary.append({
-            "cost": float(item.cost), "success": bool(item.success),
-            **transform_difference(x, candidate_x),
-        })
-    bootstrap = []
-    rng = np.random.default_rng(args.seed + 1)
-    for _ in range(args.bootstrap):
-        indexes = rng.integers(0, len(a_array), len(a_array))
-        answer = least_squares(
-            calibration_residual, best.x,
-            args=(a_array[indexes], b_array[indexes], planes, args),
-            loss="huber", f_scale=1.5, x_scale="jac", max_nfev=args.max_nfev,
-        )
-        bootstrap.append(np.r_[answer.x[:3], rpy_deg(so3_exp(answer.x[3:]))])
-    bootstrap = np.asarray(bootstrap)
-    result = {
-        "schema_version": 2,
-        "success": bool(best.success),
-        "message": best.message,
-        "convention": "T_reference_lidar maps raw LiDAR points into the supplied reference frame",
-        "equation": "A_ij X = X B_ij",
-        "measured_extrinsic_used_as_initial": False,
-        "translation_m": x[:3, 3].tolist(),
-        "rotation_rpy_deg_xyz": rpy_deg(x[:3, :3]),
-        "quaternion_xyzw": rotation_to_quat(x[:3, :3]).tolist(),
-        "matrix_4x4": x.tolist(),
-        "estimation": {"stations": stations, "pairs": len(a_array),
-                       "residuals": pair_metrics(a_array, b_array, x)},
-        "ground": {
-            "planes": len(planes),
-            "reference_origin_height_above_ground_m": args.reference_height,
-            "formula": "d_lidar - (R_X n_lidar)^T t_X - reference_height",
-        },
-        "linearized_one_sigma": {
-            "translation_m": sigma[:3].tolist(),
-            "rotation_deg": np.rad2deg(sigma[3:]).tolist(),
-            "warning": "conditional local estimate; bootstrap is the primary stability check",
-        },
-        "weighted_jacobian_condition_number": condition,
-        "solver_multistart": {
-            "runs": len(candidates), "candidates_relative_to_best": candidate_summary,
-        },
-        "bootstrap": {
-            "runs": len(bootstrap),
-            "order": ["x_m", "y_m", "z_m", "roll_deg", "pitch_deg", "yaw_deg"],
-            "std": np.std(bootstrap, axis=0, ddof=1).tolist() if len(bootstrap) > 1 else None,
-            "p025": np.quantile(bootstrap, 0.025, axis=0).tolist() if len(bootstrap) else None,
-            "p975": np.quantile(bootstrap, 0.975, axis=0).tolist() if len(bootstrap) else None,
-        },
-    }
-    output = Path(args.output)
-    output.parent.mkdir(parents=True, exist_ok=True)
-    output.write_text(json.dumps(result, ensure_ascii=False, indent=2), encoding="utf-8")
-    print(json.dumps(result, ensure_ascii=False, indent=2))
-
-
-def cmd_validate(args):
-    result = json.loads(Path(args.extrinsic).read_text(encoding="utf-8-sig"))
-    x = np.asarray(result["matrix_4x4"], float)
-    a_array, b_array, meta, stations = read_pairs(args.pairs)
-    metrics = pair_metrics(a_array, b_array, x)
-    for row, pair_meta in zip(metrics["per_pair"], meta):
-        row.update({"i": int(pair_meta[0]), "j": int(pair_meta[1])})
-    report = {
-        "role": "auxiliary check only; first-batch RTK is sparse",
-        "blind_with_respect_to_X": True,
-        "note": "No AX residual was used to select these pairs",
-        "stations": stations, "metrics": metrics,
-    }
-    output = Path(args.output)
-    output.parent.mkdir(parents=True, exist_ok=True)
-    output.write_text(json.dumps(report, ensure_ascii=False, indent=2), encoding="utf-8")
-    print(json.dumps(report, ensure_ascii=False, indent=2))
-
-
-def build_parser():
-    parser = argparse.ArgumentParser(description=__doc__)
-    commands = parser.add_subparsers(dest="command", required=True)
-    ground = commands.add_parser("ground")
-    ground.add_argument("--frames", required=True); ground.add_argument("--output", required=True)
-    ground.add_argument("--min-range", type=float, default=1.0); ground.add_argument("--max-range", type=float, default=30.0)
-    ground.add_argument("--z-min", type=float, default=-1.4); ground.add_argument("--z-max", type=float, default=-0.4)
-    ground.add_argument("--voxel", type=float, default=0.08); ground.add_argument("--distance-threshold", type=float, default=0.025)
-    ground.add_argument("--ransac-iterations", type=int, default=500); ground.add_argument("--min-inliers", type=int, default=500)
-    ground.add_argument("--max-rms", type=float, default=0.025); ground.set_defaults(func=cmd_ground)
-
-    pairs = commands.add_parser("pairs")
-    pairs.add_argument("--backend", choices=["open3d", "small_gicp"], required=True)
-    pairs.add_argument("--frames", required=True)
-    pairs.add_argument("--reference-poses", "--body", dest="reference_poses", required=True)
-    pairs.add_argument("--output", required=True); pairs.add_argument("--quality-json"); pairs.add_argument("--quality-csv")
-    pairs.add_argument("--time-offset", type=float, default=0.0)
-    pairs.add_argument("--min-stations", type=int, default=30); pairs.add_argument("--min-pairs", type=int, default=25)
-    pairs.add_argument("--min-gap", type=int, default=1); pairs.add_argument("--max-gap", type=int, default=5)
-    pairs.add_argument("--min-translation", type=float, default=0.5); pairs.add_argument("--min-rotation", type=float, default=3.0)
-    pairs.add_argument("--min-range", type=float, default=2.0); pairs.add_argument("--max-range", type=float, default=50.0)
-    pairs.add_argument("--z-min", type=float, default=-0.60); pairs.add_argument("--z-max", type=float, default=5.0)
-    pairs.add_argument("--min-roi-points", type=int, default=1000)
-    pairs.add_argument("--holdout-fraction", type=float, default=0.20)
-    pairs.add_argument("--voxels", nargs="+", type=float, default=[0.30, 0.15, 0.08])
-    pairs.add_argument("--correspondences", nargs="+", type=float, default=[1.20, 0.50, 0.25])
-    pairs.add_argument("--iterations", type=int, default=60); pairs.add_argument("--threads", type=int, default=8)
-    pairs.add_argument("--evaluation-distance", type=float, default=0.25)
-    pairs.add_argument("--min-inlier-ratio", type=float, default=0.35); pairs.add_argument("--max-inlier-rmse", type=float, default=0.16)
-    pairs.add_argument("--max-hessian-condition", type=float, default=1e8)
-    pairs.add_argument("--reverse-translation-tolerance", type=float, default=0.08)
-    pairs.add_argument("--reverse-rotation-tolerance", type=float, default=0.50)
-    pairs.add_argument("--multistart", type=int, default=2)
-    pairs.add_argument("--multistart-translation-sigma", type=float, default=0.30)
-    pairs.add_argument("--multistart-rotation-sigma", type=float, default=3.0)
-    pairs.add_argument("--multistart-translation-tolerance", type=float, default=0.08)
-    pairs.add_argument("--multistart-rotation-tolerance", type=float, default=0.50)
-    pairs.add_argument("--min-multistart-success", type=float, default=0.50)
-    pairs.add_argument("--seed", type=int, default=20260721); pairs.set_defaults(func=cmd_pairs)
-
-    calibrate = commands.add_parser("calibrate")
-    calibrate.add_argument("--pairs", required=True); calibrate.add_argument("--ground-planes", required=True)
-    calibrate.add_argument("--output", required=True)
-    calibrate.add_argument("--translation-sigma", type=float, default=0.05)
-    calibrate.add_argument("--rotation-sigma", type=float, default=0.5)
-    calibrate.add_argument("--plane-normal-sigma", type=float, default=0.02)
-    calibrate.add_argument("--plane-height-sigma", type=float, default=0.03)
-    calibrate.add_argument("--reference-height", "--body-height", dest="reference_height", type=float, default=0.8535)
-    calibrate.add_argument("--solver-multistart", type=int, default=12)
-    calibrate.add_argument("--start-translation-sigma", type=float, default=1.0)
-    calibrate.add_argument("--start-rotation-sigma", type=float, default=20.0)
-    calibrate.add_argument("--bootstrap", type=int, default=100)
-    calibrate.add_argument("--max-nfev", type=int, default=1000)
-    calibrate.add_argument("--seed", type=int, default=20260721); calibrate.set_defaults(func=cmd_calibrate)
-
-    validate = commands.add_parser("validate")
-    validate.add_argument("--pairs", required=True); validate.add_argument("--extrinsic", required=True)
-    validate.add_argument("--output", required=True); validate.set_defaults(func=cmd_validate)
-    return parser
-
-
-def main():
-    args = build_parser().parse_args()
-    args.func(args)
-
-
-if __name__ == "__main__":
-    main()
diff --git a/LiDAR_RTK_Direct_Calibration/code/visualize_pair_3d.py b/LiDAR_RTK_Direct_Calibration/code/visualize_pair_3d.py
deleted file mode 100644
index 3aa71a0..0000000
--- a/LiDAR_RTK_Direct_Calibration/code/visualize_pair_3d.py
+++ /dev/null
@@ -1,169 +0,0 @@
-#!/usr/bin/env python3
-"""Interactive 3D comparison of raw, RTK, GICP and hand-eye-predicted motion."""
-import argparse
-import json
-
-import numpy as np
-from scipy.spatial.transform import Rotation
-
-from rigorous_calibration import (
-    inverse_transform, load_stations, rotation_angle_deg, rpy_deg, transform_points,
-)
-
-
-COLORS = {
-    "target": [0.10, 0.65, 1.00],
-    "source": [1.00, 0.35, 0.05],
-}
-
-
-def cloud(o3d, points, color, voxel):
-    item = o3d.geometry.PointCloud()
-    item.points = o3d.utility.Vector3dVector(points)
-    item = item.voxel_down_sample(voxel)
-    item.paint_uniform_color(color)
-    return item
-
-
-def delta_components(reference, candidate):
-    """Components of reference^-1*candidate, plus coordinate-invariant norms."""
-    delta = inverse_transform(reference) @ candidate
-    translation = np.asarray(delta[:3, 3], float)
-    return {
-        "translation_xyz_cm": (translation * 100.0).tolist(),
-        "translation_norm_cm": float(np.linalg.norm(translation) * 100.0),
-        "rotation_rpy_deg_xyz": rpy_deg(delta[:3, :3]),
-        "rotation_angle_deg": rotation_angle_deg(delta[:3, :3]),
-    }
-
-
-def body_left_rpy(x, rpy_correction_deg):
-    correction = np.eye(4)
-    correction[:3, :3] = Rotation.from_euler(
-        "xyz", np.asarray(rpy_correction_deg, float), degrees=True
-    ).as_matrix()
-    return correction @ x
-
-
-def print_delta(name, reference, candidate):
-    item = delta_components(reference, candidate)
-    tx, ty, tz = item["translation_xyz_cm"]
-    roll, pitch, yaw = item["rotation_rpy_deg_xyz"]
-    print(
-        f"{name}: B^-1*motion translation xyz = "
-        f"[{tx:+.4f}, {ty:+.4f}, {tz:+.4f}] cm; "
-        f"rpy xyz = [{roll:+.4f}, {pitch:+.4f}, {yaw:+.4f}] deg; "
-        f"norm = {item['translation_norm_cm']:.4f} cm / "
-        f"{item['rotation_angle_deg']:.6f} deg"
-    )
-    return item
-
-
-def main():
-    import open3d as o3d
-
-    parser = argparse.ArgumentParser(description=__doc__)
-    parser.add_argument("--frames", required=True)
-    parser.add_argument("--pairs", required=True)
-    parser.add_argument("--extrinsic", required=True)
-    parser.add_argument("--pair-index", type=int, default=0)
-    parser.add_argument("--voxel", type=float, default=0.10)
-    parser.add_argument(
-        "--left-rpy-deg", nargs=3, type=float, default=[0.0, 0.0, 0.0],
-        metavar=("ROLL", "PITCH", "YAW"),
-        help="optional body-frame left correction applied as DeltaR_body * X",
-    )
-    args = parser.parse_args()
-
-    stations = load_stations(args.frames, 1.0, 60.0)
-    with np.load(args.pairs, allow_pickle=False) as data:
-        if len(stations) != len(data["station_times"]):
-            raise ValueError(
-                f"frames contain {len(stations)} stations but pair file records "
-                f"{len(data['station_times'])}"
-            )
-        if not 0 <= args.pair_index < len(data["A"]):
-            raise IndexError(
-                f"pair-index {args.pair_index} outside [0,{len(data['A']) - 1}]"
-            )
-        a_ij = np.asarray(data["A"][args.pair_index], float)
-        b_gicp = np.asarray(data["B"][args.pair_index], float)
-        i, j = np.asarray(data["meta"][args.pair_index, :2], int)
-
-    with open(args.extrinsic, encoding="utf-8-sig") as stream:
-        result = json.load(stream)
-    x = np.asarray(result["matrix_4x4"], float)
-    b_calibrated = inverse_transform(x) @ a_ij @ x
-
-    transforms = {
-        "1 raw": np.eye(4),
-        "2 RTK initial (X0=I)": a_ij,
-        "3 GICP B": b_gicp,
-        "4 calibrated X^-1 A X": b_calibrated,
-    }
-    correction = np.asarray(args.left_rpy_deg, float)
-    if np.any(np.abs(correction) > 0.0):
-        x_test = body_left_rpy(x, correction)
-        transforms[
-            f"5 test body-left RPY {correction.tolist()} deg"
-        ] = inverse_transform(x_test) @ a_ij @ x_test
-
-    target = stations[i][3]
-    source = stations[j][3]
-    print(f"pair_index={args.pair_index}, station {i} <- {j}")
-    print("blue = target station i; orange = source station j after selected transform")
-    print("keys: 1 raw | 2 RTK initial | 3 GICP | 4 calibrated | 5 test correction | Q/Esc exit")
-    print(
-        "IMPORTANT: delta xyz/rpy are components of B^-1*(X^-1*A*X), expressed "
-        "in station-j LiDAR coordinates; screen-left/right depends on the 3D camera view."
-    )
-    baseline = print_delta("mode 4 minus mode 3", b_gicp, b_calibrated)
-    roll, pitch, yaw = np.abs(baseline["rotation_rpy_deg_xyz"])
-    if max(roll, pitch) > max(0.10, 2.0 * yaw):
-        print("diagnosis: roll/pitch components dominate yaw; do not prioritize yaw tuning for this pair.")
-    tx, ty, tz = np.abs(baseline["translation_xyz_cm"])
-    if tz > max(tx, ty):
-        print("diagnosis: the largest translation component is relative Z, not lateral XY.")
-    body_up = np.array([0.0, 0.0, 1.0])
-    if np.linalg.norm(a_ij[:3, :3] @ body_up - body_up) < 1e-8:
-        print(
-            "observability: this A preserves the body Z axis, so body-left X.z "
-            "translation is unobservable from this pair; use ground/external height constraints."
-        )
-    if "5 test body-left RPY " + str(correction.tolist()) + " deg" in transforms:
-        print_delta("mode 5 minus mode 3", b_gicp, list(transforms.values())[-1])
-
-    viewer = o3d.visualization.VisualizerWithKeyCallback()
-    viewer.create_window("Rigorous LiDAR registration inspection - 3D", 1400, 900)
-    target_cloud = cloud(o3d, target, COLORS["target"], args.voxel)
-    source_cloud = cloud(o3d, source, COLORS["source"], args.voxel)
-    viewer.add_geometry(target_cloud)
-    viewer.add_geometry(source_cloud)
-    axes = o3d.geometry.TriangleMesh.create_coordinate_frame(size=1.0)
-    viewer.add_geometry(axes)
-    current = np.eye(4)
-
-    def select(name):
-        def callback(vis):
-            nonlocal current
-            desired = transforms[name]
-            source_cloud.transform(desired @ inverse_transform(current))
-            current = desired
-            vis.update_geometry(source_cloud)
-            if name == "3 GICP B":
-                print(f"{name}: reference registration B; delta = 0")
-            else:
-                print_delta(name + " minus mode 3", b_gicp, desired)
-            return False
-        return callback
-
-    for key, name in zip((ord("1"), ord("2"), ord("3"), ord("4"), ord("5")), transforms):
-        viewer.register_key_callback(key, select(name))
-    viewer.get_render_option().background_color = np.array([0.02, 0.02, 0.02])
-    viewer.get_render_option().point_size = 2.0
-    viewer.run()
-    viewer.destroy_window()
-
-
-if __name__ == "__main__":
-    main()
diff --git a/LiDAR_RTK_Direct_Calibration/requirements.txt b/LiDAR_RTK_Direct_Calibration/requirements.txt
deleted file mode 100644
index 9f8e5e8..0000000
--- a/LiDAR_RTK_Direct_Calibration/requirements.txt
+++ /dev/null
@@ -1,4 +0,0 @@
-numpy>=1.26
-scipy>=1.11
-open3d>=0.18
-small-gicp
diff --git a/LiDAR_RTK_Direct_Calibration/results/README.md b/LiDAR_RTK_Direct_Calibration/results/README.md
deleted file mode 100644
index e43ace6..0000000
--- a/LiDAR_RTK_Direct_Calibration/results/README.md
+++ /dev/null
@@ -1,5 +0,0 @@
-# results目录
-
-`reference_data4/`是本仓库附带的精简参考结果。新的运行结果应写到仓库外目录或`outputs/`，不要覆盖参考结果。
-
-参考结果保留最终矩阵、共识B、两后端精筛B、逐对CSV/筛选审计和地面平面；未保留原始点云、逐帧combined数据、冗长的初筛JSON和带本机绝对路径的过程文件。
diff --git a/LiDAR_RTK_Direct_Calibration/run/README.md b/LiDAR_RTK_Direct_Calibration/run/README.md
deleted file mode 100644
index 120bf1c..0000000
--- a/LiDAR_RTK_Direct_Calibration/run/README.md
+++ /dev/null
@@ -1,14 +0,0 @@
-# run目录
-
-根README包含完整复现命令；这里仅列入口职责。
-
-| 脚本 | 用途 |
-|---|---|
-| `run_full_pipeline.ps1` | 从逐站LiDAR dlog、RTK rscap、IMU rscap一直运行到最终`T_RTK_lidar` |
-| `export_multisensor_stations.ps1` | 解析原始三传感器数据并按LiDAR帧生成combined NPZ |
-| `prepare_multisensor_dataset.ps1` | 每站选一帧，生成yaw-only RTK参考轨迹和`frames_all` |
-| `run_direct_rtk_lidar.ps1` | 从combined数据运行RTK直接标定和最终结果封装 |
-| `run_single_dataset.ps1` | 执行地面、两个GICP后端、精筛、共识和AX=XB求解 |
-| `view_result.ps1` | 打开3D运动对对比并打印数值增量 |
-
-所有路径均为命令行参数；默认生成目录`work/`和`outputs/`不会提交Git。
diff --git a/LiDAR_RTK_Direct_Calibration/run/export_multisensor_stations.ps1 b/LiDAR_RTK_Direct_Calibration/run/export_multisensor_stations.ps1
deleted file mode 100644
index e96be10..0000000
--- a/LiDAR_RTK_Direct_Calibration/run/export_multisensor_stations.ps1
+++ /dev/null
@@ -1,89 +0,0 @@
-param(
-    [Parameter(Mandatory = $true)][string]$DataRoot,
-    [Parameter(Mandatory = $true)][string]$OutputRoot,
-    [Parameter(Mandatory = $true)][string]$RtkCapture,
-    [Parameter(Mandatory = $true)][string]$ImuCapture,
-    [string]$LidarObject = "frontlidar",
-    [string]$Timezone = "+08:00",
-    [string[]]$StationNames = @(),
-    [int]$Stride = 1,
-    [double]$RtkMaxDtMs = 150.0,
-    [double]$ImuBeforeMs = 100.0,
-    [double]$ImuAfterMs = 100.0,
-    [switch]$SkipLidarExport,
-    [switch]$SkipSerialParsing
-)
-
-$ErrorActionPreference = "Stop"
-$RepoRoot = Split-Path -Parent $PSScriptRoot
-$Exporter = Join-Path $RepoRoot "tools\frontlidar_dlog_export.py"
-$Builder = Join-Path $RepoRoot "tools\build_multisensor_npz.py"
-$Parser = Join-Path $RepoRoot "tools\rscap_v2\parse_rtk_imu_v2.py"
-$Auditor = Join-Path $RepoRoot "tools\rscap_v2\audit_capture_v2.py"
-$ExportRoot = Join-Path $OutputRoot "export"
-$ParsedRoot = Join-Path $OutputRoot "parsed"
-$CombinedRoot = Join-Path $OutputRoot "combined"
-
-function Run-Python {
-    param([string]$Stage, [string[]]$Arguments)
-    Write-Host "[$Stage]"
-    & python @Arguments
-    if ($LASTEXITCODE -ne 0) {
-        throw "$Stage failed with Python exit code $LASTEXITCODE"
-    }
-}
-
-foreach ($Path in @($DataRoot, $RtkCapture, $ImuCapture)) {
-    if (-not (Test-Path -LiteralPath $Path)) { throw "Input does not exist: $Path" }
-}
-if ($Stride -lt 1) { throw "Stride must be at least 1" }
-
-if ($StationNames.Count -gt 0) {
-    $Stations = @($StationNames | ForEach-Object { Get-Item -LiteralPath (Join-Path $DataRoot $_) })
-} else {
-    $Stations = @(Get-ChildItem -LiteralPath $DataRoot -Directory | Where-Object {
-        (Test-Path -LiteralPath (Join-Path $_.FullName "dobject")) -and
-        (Test-Path -LiteralPath (Join-Path $_.FullName "dobject_recording"))
-    } | Sort-Object Name)
-}
-if ($Stations.Count -eq 0) { throw "No station directory containing dobject and dobject_recording was found" }
-
-New-Item -ItemType Directory -Force -Path $OutputRoot | Out-Null
-if (-not $SkipSerialParsing) {
-    New-Item -ItemType Directory -Force -Path $ParsedRoot | Out-Null
-    Run-Python "capture audit" @($Auditor, $RtkCapture, $ImuCapture, "--out", (Join-Path $OutputRoot "capture_audit.json"))
-    Run-Python "RTK/IMU parse" @($Parser, "--rtk", $RtkCapture, "--imu", $ImuCapture, "--out", $ParsedRoot)
-}
-
-foreach ($Station in $Stations) {
-    $StationOut = Join-Path $ExportRoot $Station.Name
-    if (-not $SkipLidarExport) {
-        Run-Python "LiDAR station $($Station.Name)" @(
-            $Exporter, "--dlog", $Station.FullName, "--out", $StationOut,
-            "--object", $LidarObject, "--format", "npz", "--timezone", $Timezone,
-            "--stride", "$Stride", "--compress", "--skip-rtk", "--write-reports", "--resume"
-        )
-    }
-    if (-not (Test-Path -LiteralPath (Join-Path $StationOut "frames"))) {
-        throw "Exported frame directory is absent for station $($Station.Name): $StationOut"
-    }
-}
-
-$BuildArgs = @($Builder)
-foreach ($Station in $Stations) {
-    $Frames = Join-Path (Join-Path $ExportRoot $Station.Name) "frames"
-    $BuildArgs += @("--lidar", "$($Station.Name)=$Frames")
-}
-$BuildArgs += @(
-    "--rtk", (Join-Path $ParsedRoot "rtk.jsonl"),
-    "--imu", (Join-Path $ParsedRoot "imu.jsonl"),
-    "--out", $CombinedRoot,
-    "--rtk-max-dt-ms", "$RtkMaxDtMs",
-    "--imu-before-ms", "$ImuBeforeMs",
-    "--imu-after-ms", "$ImuAfterMs",
-    "--overwrite"
-)
-Run-Python "LiDAR/RTK/IMU association" $BuildArgs
-
-Write-Host "Completed stations: $($Stations.Count)"
-Write-Host "Combined NPZ: $CombinedRoot"
diff --git a/LiDAR_RTK_Direct_Calibration/run/prepare_multisensor_dataset.ps1 b/LiDAR_RTK_Direct_Calibration/run/prepare_multisensor_dataset.ps1
deleted file mode 100644
index a5b07a9..0000000
--- a/LiDAR_RTK_Direct_Calibration/run/prepare_multisensor_dataset.ps1
+++ /dev/null
@@ -1,22 +0,0 @@
-param(
-    [Parameter(Mandatory = $true)][string]$CombinedRoot,
-    [Parameter(Mandatory = $true)][string]$Output,
-    [Parameter(Mandatory = $true)][double]$HeadingOffsetDeg,
-    [Parameter(Mandatory = $true)][double[]]$AntennaLever,
-    [string]$PoseName = "rtk_gga_raw_heading",
-    [int]$MinStations = 30,
-    [int]$ExpectedStations = 0,
-    [double]$HeadingStdLimitDeg = 0.5,
-    [switch]$Overwrite
-)
-
-$ErrorActionPreference = "Stop"
-if ($AntennaLever.Count -ne 3) { throw "AntennaLever must contain X,Y,Z in body coordinates" }
-$Repo = Split-Path -Parent $PSScriptRoot
-$Args = @((Join-Path $Repo "tools\prepare_multisensor_station_dataset.py"), "--combined-root", $CombinedRoot,
-    "--output", $Output, "--pose-name", $PoseName, "--heading-offset-deg", "$HeadingOffsetDeg", "--antenna-lever") +
-    @($AntennaLever | ForEach-Object { "$_" }) + @("--min-stations", "$MinStations",
-    "--expected-stations", "$ExpectedStations", "--heading-std-limit-deg", "$HeadingStdLimitDeg")
-if ($Overwrite) { $Args += "--overwrite" }
-& python @Args
-if ($LASTEXITCODE -ne 0) { throw "Multisensor dataset preparation failed" }
diff --git a/LiDAR_RTK_Direct_Calibration/run/run_single_dataset.ps1 b/LiDAR_RTK_Direct_Calibration/run/run_single_dataset.ps1
deleted file mode 100644
index 3bf3e53..0000000
--- a/LiDAR_RTK_Direct_Calibration/run/run_single_dataset.ps1
+++ /dev/null
@@ -1,70 +0,0 @@
-param(
-    [Parameter(Mandatory = $true)][string]$Prepared,
-    [Parameter(Mandatory = $true)][string]$OutputRoot,
-    [string]$ReferencePoseFile = "reference_poses_rtk_gga_raw_heading.csv",
-    [double]$ReferenceHeight = 0.8535,
-    [int]$MinPairs = 20,
-    [int]$Bootstrap = 100
-)
-
-$ErrorActionPreference = "Stop"
-$Repo = Split-Path -Parent $PSScriptRoot
-$Code = Join-Path $Repo "code\rigorous_calibration.py"
-$Refine = Join-Path $Repo "code\refine_pairs.py"
-$Consensus = Join-Path $Repo "code\cross_backend_filter.py"
-$Frames = Join-Path $Prepared "frames_all"
-$ReferencePoses = Join-Path $Prepared $ReferencePoseFile
-$Common = Join-Path $OutputRoot "common"
-$Open = Join-Path $OutputRoot "open3d_gicp"
-$Small = Join-Path $OutputRoot "small_gicp"
-$ConsensusOut = Join-Path $OutputRoot "consensus"
-
-function Run-Python {
-    param([string]$Stage, [string[]]$Arguments)
-    Write-Host "[$Stage]"
-    & python @Arguments
-    if ($LASTEXITCODE -ne 0) { throw "$Stage failed with Python exit code $LASTEXITCODE" }
-}
-
-foreach ($Path in @($Frames, $ReferencePoses)) {
-    if (-not (Test-Path -LiteralPath $Path)) { throw "Input does not exist: $Path" }
-}
-New-Item -ItemType Directory -Force -Path $Common,$Open,$Small,$ConsensusOut | Out-Null
-
-$Ground = Join-Path $Common "ground_planes.csv"
-Run-Python "ground planes" @($Code, "ground", "--frames", $Frames, "--output", $Ground)
-
-foreach ($Backend in @("small_gicp", "open3d")) {
-    $Directory = if ($Backend -eq "small_gicp") { $Small } else { $Open }
-    $Raw = Join-Path $Directory "B_estimation.npz"
-    $QualityJson = Join-Path $Directory "B_quality.json"
-    $QualityCsv = Join-Path $Directory "B_quality.csv"
-    $PairArgs = @($Code, "pairs", "--backend", $Backend, "--frames", $Frames, "--reference-poses", $ReferencePoses,
-                  "--output", $Raw, "--quality-json", $QualityJson, "--quality-csv", $QualityCsv,
-                  "--min-pairs", "$MinPairs")
-    if ($Backend -eq "open3d") { $PairArgs += @("--max-gap", "3", "--multistart", "1", "--iterations", "40") }
-    Run-Python "$Backend pairs" $PairArgs
-    Run-Python "$Backend X-independent refinement" @(
-        $Refine, "--pairs", $Raw, "--quality-json", $QualityJson,
-        "--output", (Join-Path $Directory "B_refined.npz"), "--min-pairs", "$MinPairs"
-    )
-    Run-Python "$Backend calibration" @(
-        $Code, "calibrate", "--pairs", (Join-Path $Directory "B_refined.npz"),
-        "--ground-planes", $Ground, "--reference-height", "$ReferenceHeight",
-        "--bootstrap", "$Bootstrap", "--output", (Join-Path $Directory "extrinsic.json")
-    )
-}
-
-$ConsensusPairs = Join-Path $ConsensusOut "B_consensus.npz"
-Run-Python "cross-backend consensus" @(
-    $Consensus, "--open3d-pairs", (Join-Path $Open "B_refined.npz"),
-    "--small-pairs", (Join-Path $Small "B_refined.npz"),
-    "--output", $ConsensusPairs, "--min-pairs", "$MinPairs"
-)
-Run-Python "consensus calibration" @(
-    $Code, "calibrate", "--pairs", $ConsensusPairs, "--ground-planes", $Ground,
-    "--reference-height", "$ReferenceHeight", "--bootstrap", "$Bootstrap",
-    "--output", (Join-Path $ConsensusOut "extrinsic.json")
-)
-
-Write-Host "Calibration results: $OutputRoot"
diff --git a/LiDAR_RTK_Direct_Calibration/run/view_result.ps1 b/LiDAR_RTK_Direct_Calibration/run/view_result.ps1
deleted file mode 100644
index e513e61..0000000
--- a/LiDAR_RTK_Direct_Calibration/run/view_result.ps1
+++ /dev/null
@@ -1,19 +0,0 @@
-param(
-    [Parameter(Mandatory = $true)][string]$Frames,
-    [Parameter(Mandatory = $true)][string]$Pairs,
-    [Parameter(Mandatory = $true)][string]$Extrinsic,
-    [int]$PairIndex = 0,
-    [double]$LeftRollDeg = 0.0,
-    [double]$LeftPitchDeg = 0.0,
-    [double]$LeftYawDeg = 0.0
-)
-
-$ErrorActionPreference = "Stop"
-$Repo = Split-Path -Parent $PSScriptRoot
-foreach ($Path in @($Frames, $Pairs, $Extrinsic)) {
-    if (-not (Test-Path -LiteralPath $Path)) { throw "Input does not exist: $Path" }
-}
-& python (Join-Path $Repo "code\visualize_pair_3d.py") `
-    --frames $Frames --pairs $Pairs --extrinsic $Extrinsic --pair-index $PairIndex `
-    --left-rpy-deg $LeftRollDeg $LeftPitchDeg $LeftYawDeg
-if ($LASTEXITCODE -ne 0) { throw "Visualization failed with Python exit code $LASTEXITCODE" }
diff --git a/LiDAR_RTK_Direct_Calibration/tools/README.md b/LiDAR_RTK_Direct_Calibration/tools/README.md
deleted file mode 100644
index c670433..0000000
--- a/LiDAR_RTK_Direct_Calibration/tools/README.md
+++ /dev/null
@@ -1,11 +0,0 @@
-# tools目录
-
-| 文件 | 输入→输出 |
-|---|---|
-| `frontlidar_dlog_export.py` | LiDAR dlog → 逐帧原始点云NPZ；时间来自DObject post tick |
-| `rscap_v2/parse_rtk_imu_v2.py` | RTK/IMU rscap → JSONL，保存校验状态、主机时间、GNSS/IMU设备字段和原始报文 |
-| `rscap_v2/audit_capture_v2.py` | 检查rscap结构、时间范围和记录统计 |
-| `build_multisensor_npz.py` | 按LiDAR帧最近邻关联GGA/heading，并附加IMU时间窗 → combined NPZ |
-| `prepare_multisensor_station_dataset.py` | combined NPZ → 每站一帧`frames_all`和`reference_poses_*.csv` |
-
-当前标定只使用LiDAR和RTK；IMU保持原始传感器坐标，不参与点云去畸变或外参求解。prepared阶段对站内有效RTK取平均、对heading取圆均值，并选择有效帧序列的中间LiDAR帧。
diff --git a/LiDAR_RTK_Direct_Calibration/tools/build_multisensor_npz.py b/LiDAR_RTK_Direct_Calibration/tools/build_multisensor_npz.py
deleted file mode 100644
index 2da2043..0000000
--- a/LiDAR_RTK_Direct_Calibration/tools/build_multisensor_npz.py
+++ /dev/null
@@ -1,312 +0,0 @@
-#!/usr/bin/env python3
-"""Build one LiDAR-centric NPZ per frame with matched RTK and an IMU window.
-
-Inputs are LiDAR frame NPZ files from frontlidar_dlog_export.py and parsed
-RTK/IMU JSONL files from parse_rtk_imu_v2.py.  Raw .rscap files remain the
-traceability source; this script never modifies them.
-"""
-
-from __future__ import annotations
-
-import argparse
-import csv
-import json
-from pathlib import Path
-from typing import Any
-
-import numpy as np
-
-
-GPS_EPOCH_UNIX_NS = 315964800 * 1_000_000_000
-
-
-def parse_named_path(text: str) -> tuple[str, Path]:
-    if "=" not in text:
-        raise argparse.ArgumentTypeError("expected NAME=PATH")
-    name, raw_path = text.split("=", 1)
-    if not name.strip():
-        raise argparse.ArgumentTypeError("segment name is empty")
-    return name.strip(), Path(raw_path)
-
-
-def parse_args() -> argparse.Namespace:
-    parser = argparse.ArgumentParser()
-    parser.add_argument(
-        "--lidar",
-        type=parse_named_path,
-        action="append",
-        required=True,
-        metavar="NAME=FRAMES_DIR",
-        help="Repeat for each LiDAR segment; directory contains exported *.npz frames.",
-    )
-    parser.add_argument("--rtk", type=Path, action="append", required=True, help="Parsed rtk.jsonl; repeat per session.")
-    parser.add_argument("--imu", type=Path, action="append", required=True, help="Parsed imu.jsonl; repeat per session.")
-    parser.add_argument("--out", type=Path, required=True)
-    parser.add_argument("--rtk-max-dt-ms", type=float, default=150.0)
-    parser.add_argument("--imu-before-ms", type=float, default=100.0)
-    parser.add_argument("--imu-after-ms", type=float, default=100.0)
-    parser.add_argument("--gps-utc-leap-seconds", type=int, default=18)
-    parser.add_argument("--overwrite", action="store_true")
-    return parser.parse_args()
-
-
-def load_jsonl(paths: list[Path]) -> list[dict[str, Any]]:
-    rows: list[dict[str, Any]] = []
-    for source_index, path in enumerate(paths):
-        source_file = str(path.resolve())
-        with path.open("r", encoding="utf-8") as stream:
-            for line_number, line in enumerate(stream, start=1):
-                if not line.strip():
-                    continue
-                row = json.loads(line)
-                row["_source_file"] = source_file
-                row["_source_index"] = source_index
-                row["_source_line"] = line_number
-                rows.append(row)
-    return rows
-
-
-def utf8_array(value: Any) -> np.ndarray:
-    return np.frombuffer(str(value if value is not None else "").encode("utf-8"), dtype=np.uint8)
-
-
-def scalar(array: np.ndarray) -> Any:
-    return array.reshape(-1)[0].item()
-
-
-def nearest_index(times: np.ndarray, target: int) -> int:
-    if not len(times):
-        return -1
-    right = int(np.searchsorted(times, target, side="left"))
-    candidates = [index for index in (right - 1, right) if 0 <= index < len(times)]
-    return min(candidates, key=lambda index: abs(int(times[index]) - target))
-
-
-def estimate_imu_times(rows: list[dict[str, Any]]) -> list[dict[str, Any]]:
-    """Recover 100 Hz timing inside each serial chunk from device timestamps.
-
-    A capture chunk has one host receive timestamp but may contain several IMU
-    frames.  The last frame is anchored to the chunk receive time and earlier
-    frames are moved backwards by their device timestamp difference.
-    """
-    groups: dict[tuple[int, int], list[dict[str, Any]]] = {}
-    for row in rows:
-        if not row.get("crc_valid") or row.get("device_timestamp_ms") is None:
-            continue
-        key = (int(row["_source_index"]), int(row.get("source_chunk_sequence_last", -1)))
-        groups.setdefault(key, []).append(row)
-    result: list[dict[str, Any]] = []
-    for group in groups.values():
-        group.sort(key=lambda row: (int(row["device_timestamp_ms"]), int(row["_source_line"])))
-        last_device = int(group[-1]["device_timestamp_ms"])
-        host_ns = int(group[-1]["host_receive_utc_ns"])
-        for row in group:
-            delta_ms = (last_device - int(row["device_timestamp_ms"])) & 0xFFFFFFFF
-            if delta_ms > 60_000:
-                delta_ms = 0
-            copied = dict(row)
-            copied["estimated_time_ns"] = host_ns - delta_ms * 1_000_000
-            result.append(copied)
-    result.sort(key=lambda row: int(row["estimated_time_ns"]))
-    return result
-
-
-def gnss_utc_ns(row: dict[str, Any], leap_seconds: int) -> int | None:
-    week, tow_ms = row.get("gnss_week"), row.get("gnss_tow_ms")
-    if week is None or tow_ms is None:
-        return None
-    seconds = int(week) * 604800 + float(tow_ms) / 1000.0 - leap_seconds
-    return GPS_EPOCH_UNIX_NS + int(round(seconds * 1_000_000_000))
-
-
-def numeric_array(rows: list[dict[str, Any]], key: str, dtype: Any, default: Any) -> np.ndarray:
-    return np.asarray([row.get(key, default) if row.get(key) is not None else default for row in rows], dtype=dtype)
-
-
-def raw_frame_matrix(rows: list[dict[str, Any]]) -> tuple[np.ndarray, np.ndarray]:
-    frames = [bytes.fromhex(str(row.get("raw_frame_hex", ""))) for row in rows]
-    lengths = np.asarray([len(frame) for frame in frames], dtype=np.int32)
-    width = max(lengths, default=0)
-    matrix = np.zeros((len(frames), width), dtype=np.uint8)
-    for index, frame in enumerate(frames):
-        matrix[index, : len(frame)] = np.frombuffer(frame, dtype=np.uint8)
-    return matrix, lengths
-
-
-def add_rtk(values: dict[str, np.ndarray], prefix: str, row: dict[str, Any] | None, dt_ns: int | None) -> None:
-    values[f"{prefix}_valid"] = np.asarray([row is not None], dtype=np.uint8)
-    values[f"{prefix}_dt_ns"] = np.asarray([dt_ns or 0], dtype=np.int64)
-    values[f"{prefix}_host_receive_utc_ns"] = np.asarray([0], dtype=np.int64)
-    values[f"{prefix}_raw_utf8"] = utf8_array("")
-    values[f"{prefix}_source_file_utf8"] = utf8_array("")
-    values[f"{prefix}_source_raw_file_offset"] = np.asarray([-1], dtype=np.int64)
-    values[f"{prefix}_source_raw_byte_length"] = np.asarray([0], dtype=np.int32)
-    if row is None:
-        return
-    values[f"{prefix}_host_receive_utc_ns"] = np.asarray([row.get("host_receive_utc_ns", 0)], dtype=np.int64)
-    values[f"{prefix}_raw_utf8"] = utf8_array(row.get("raw_line", ""))
-    values[f"{prefix}_source_file_utf8"] = utf8_array(row.get("_source_file", ""))
-    values[f"{prefix}_source_raw_file_offset"] = np.asarray([row.get("source_raw_file_offset", -1)], dtype=np.int64)
-    values[f"{prefix}_source_raw_byte_length"] = np.asarray([row.get("source_raw_byte_length", 0)], dtype=np.int32)
-
-
-def initialize_rtk_measurements(values: dict[str, np.ndarray]) -> None:
-    for key, dtype, default in (
-        ("lat_deg", np.float64, np.nan), ("lon_deg", np.float64, np.nan),
-        ("altitude_m", np.float64, np.nan), ("hdop", np.float64, np.nan),
-        ("fix_quality", np.int32, -1), ("gga_satellites", np.int32, -1),
-        ("differential_age_s", np.float64, np.nan),
-        ("gnss_week", np.int32, -1), ("gnss_tow_ms", np.int64, -1),
-        ("baseline_length_m", np.float64, np.nan), ("raw_heading_deg", np.float64, np.nan),
-        ("pitch_deg", np.float64, np.nan), ("heading_stddev_deg", np.float64, np.nan),
-        ("pitch_stddev_deg", np.float64, np.nan), ("heading_satellites", np.int32, -1),
-        ("solution_satellites", np.int32, -1),
-    ):
-        values[f"rtk_{key}"] = np.asarray([default], dtype=dtype)
-    values["rtk_fixed"] = np.asarray([0], dtype=np.uint8)
-    values["rtk_heading_solution_utf8"] = utf8_array("")
-    values["rtk_heading_gnss_utc_ns"] = np.asarray([0], dtype=np.int64)
-    values["rtk_heading_host_minus_gnss_ns"] = np.asarray([0], dtype=np.int64)
-
-def main() -> int:
-    args = parse_args()
-    if args.out.exists() and any(args.out.iterdir()) and not args.overwrite:
-        raise FileExistsError(f"{args.out} is non-empty; pass --overwrite")
-    frames_out = args.out / "frames"
-    frames_out.mkdir(parents=True, exist_ok=True)
-
-    rtk_rows = load_jsonl(args.rtk)
-    gga = sorted(
-        [row for row in rtk_rows if row.get("type") == "GGA" and row.get("checksum_valid") and row.get("lat_deg") is not None],
-        key=lambda row: int(row["host_receive_utc_ns"]),
-    )
-    heading = sorted(
-        [row for row in rtk_rows if row.get("type") == "UNIHEADINGA" and row.get("checksum_valid") and row.get("heading_valid")],
-        key=lambda row: int(row["host_receive_utc_ns"]),
-    )
-    imu = estimate_imu_times(load_jsonl(args.imu))
-    gga_times = np.asarray([int(row["host_receive_utc_ns"]) for row in gga], dtype=np.int64)
-    heading_times = np.asarray([int(row["host_receive_utc_ns"]) for row in heading], dtype=np.int64)
-    imu_times = np.asarray([int(row["estimated_time_ns"]) for row in imu], dtype=np.int64)
-
-    manifest: list[dict[str, Any]] = []
-    global_index = 0
-    max_rtk_ns = int(args.rtk_max_dt_ms * 1_000_000)
-    before_ns = int(args.imu_before_ms * 1_000_000)
-    after_ns = int(args.imu_after_ms * 1_000_000)
-
-    for segment_name, frame_dir in args.lidar:
-        frame_paths = sorted(frame_dir.glob("*.npz"))
-        if not frame_paths:
-            raise FileNotFoundError(f"no NPZ frames under {frame_dir}")
-        for segment_index, source in enumerate(frame_paths):
-            with np.load(source, allow_pickle=False) as frame:
-                values = {key: np.asarray(frame[key]) for key in frame.files}
-            lidar_time_ns = int(scalar(values["unix_time_ns"]))
-
-            gga_index = nearest_index(gga_times, lidar_time_ns)
-            heading_index = nearest_index(heading_times, lidar_time_ns)
-            gga_row = gga[gga_index] if gga_index >= 0 else None
-            heading_row = heading[heading_index] if heading_index >= 0 else None
-            gga_dt = int(gga_times[gga_index]) - lidar_time_ns if gga_index >= 0 else None
-            heading_dt = int(heading_times[heading_index]) - lidar_time_ns if heading_index >= 0 else None
-            gga_ok = gga_row is not None and abs(gga_dt or 0) <= max_rtk_ns
-            heading_ok = heading_row is not None and abs(heading_dt or 0) <= max_rtk_ns
-            add_rtk(values, "rtk_gga", gga_row if gga_ok else None, gga_dt)
-            add_rtk(values, "rtk_heading", heading_row if heading_ok else None, heading_dt)
-            initialize_rtk_measurements(values)
-
-            if gga_ok and gga_row:
-                for key, dtype, default in (
-                    ("lat_deg", np.float64, np.nan), ("lon_deg", np.float64, np.nan),
-                    ("altitude_m", np.float64, np.nan), ("hdop", np.float64, np.nan),
-                    ("fix_quality", np.int32, -1), ("gga_satellites", np.int32, -1),
-                    ("differential_age_s", np.float64, np.nan),
-                ):
-                    values[f"rtk_{key}"] = np.asarray([gga_row.get(key, default)], dtype=dtype)
-                values["rtk_gga_satellites"] = np.asarray([gga_row.get("satellites", -1)], dtype=np.int32)
-                values["rtk_fixed"] = np.asarray([int(gga_row.get("fix_quality", -1)) in {4, 5}], dtype=np.uint8)
-            if heading_ok and heading_row:
-                for key, dtype, default in (
-                    ("gnss_week", np.int32, -1), ("gnss_tow_ms", np.int64, -1),
-                    ("baseline_length_m", np.float64, np.nan), ("raw_heading_deg", np.float64, np.nan),
-                    ("pitch_deg", np.float64, np.nan), ("heading_stddev_deg", np.float64, np.nan),
-                    ("pitch_stddev_deg", np.float64, np.nan),
-                    ("solution_satellites", np.int32, -1),
-                ):
-                    values[f"rtk_{key}"] = np.asarray([heading_row.get(key, default)], dtype=dtype)
-                values["rtk_heading_satellites"] = np.asarray([heading_row.get("satellites", -1)], dtype=np.int32)
-                values["rtk_heading_solution_utf8"] = utf8_array(heading_row.get("heading_solution", ""))
-                device_ns = gnss_utc_ns(heading_row, args.gps_utc_leap_seconds)
-                values["rtk_heading_gnss_utc_ns"] = np.asarray([device_ns or 0], dtype=np.int64)
-                values["rtk_heading_host_minus_gnss_ns"] = np.asarray(
-                    [int(heading_row["host_receive_utc_ns"]) - device_ns if device_ns is not None else 0], dtype=np.int64
-                )
-
-            left = int(np.searchsorted(imu_times, lidar_time_ns - before_ns, side="left"))
-            right = int(np.searchsorted(imu_times, lidar_time_ns + after_ns, side="right"))
-            window = imu[left:right]
-            values["imu_window_count"] = np.asarray([len(window)], dtype=np.int32)
-            values["imu_valid"] = np.asarray([bool(window)], dtype=np.uint8)
-            values["imu_time_ns"] = numeric_array(window, "estimated_time_ns", np.int64, 0)
-            values["imu_host_receive_utc_ns"] = numeric_array(window, "host_receive_utc_ns", np.int64, 0)
-            for key in ("device_timestamp_ms", "pps_sync_stamp_ms", "tag"):
-                values[f"imu_{key}"] = numeric_array(window, key, np.int64, -1)
-            for key in (
-                "temperature_c", "air_pressure_pa", "accel_x_mps2", "accel_y_mps2", "accel_z_mps2",
-                "gyro_x_radps", "gyro_y_radps", "gyro_z_radps", "mag_x_ut", "mag_y_ut", "mag_z_ut",
-                "roll_deg", "pitch_deg", "yaw_deg", "quaternion_w", "quaternion_x", "quaternion_y", "quaternion_z",
-            ):
-                values[f"imu_{key}"] = numeric_array(window, key, np.float64, np.nan)
-            values["imu_source_index"] = numeric_array(window, "_source_index", np.int32, -1)
-            values["imu_source_raw_file_offset"] = numeric_array(window, "source_raw_file_offset", np.int64, -1)
-            raw_matrix, raw_lengths = raw_frame_matrix(window)
-            values["imu_raw_frame_bytes"] = raw_matrix
-            values["imu_raw_frame_length"] = raw_lengths
-            values["imu_source_files_json_utf8"] = utf8_array(json.dumps([str(path.resolve()) for path in args.imu], ensure_ascii=False))
-            values["source_lidar_file_utf8"] = utf8_array(source.resolve())
-            values["segment_name_utf8"] = utf8_array(segment_name)
-
-            output = frames_out / f"{segment_name}_{segment_index:06d}.npz"
-            np.savez_compressed(output, **values)
-            manifest.append({
-                "global_index": global_index,
-                "segment": segment_name,
-                "segment_index": segment_index,
-                "output": str(output.relative_to(args.out)),
-                "source_lidar": str(source.resolve()),
-                "lidar_time_ns": lidar_time_ns,
-                "rtk_gga_dt_ns": gga_dt,
-                "rtk_heading_dt_ns": heading_dt,
-                "rtk_valid": gga_ok,
-                "heading_valid": heading_ok,
-                "rtk_fix_quality": gga_row.get("fix_quality") if gga_ok and gga_row else None,
-                "rtk_fixed": bool(gga_ok and gga_row and int(gga_row.get("fix_quality", -1)) in {4, 5}),
-                "imu_window_count": len(window),
-            })
-            global_index += 1
-
-    fields = sorted({key for row in manifest for key in row})
-    with (args.out / "manifest.csv").open("w", encoding="utf-8", newline="") as stream:
-        writer = csv.DictWriter(stream, fieldnames=fields)
-        writer.writeheader()
-        writer.writerows(manifest)
-    summary = {
-        "frames": len(manifest),
-        "segments": {name: sum(row["segment"] == name for row in manifest) for name, _ in args.lidar},
-        "rtk_valid": sum(bool(row["rtk_valid"]) for row in manifest),
-        "heading_valid": sum(bool(row["heading_valid"]) for row in manifest),
-        "rtk_fixed": sum(bool(row["rtk_fixed"]) for row in manifest),
-        "imu_window_nonempty": sum(int(row["imu_window_count"]) > 0 for row in manifest),
-        "rtk_max_dt_ms": args.rtk_max_dt_ms,
-        "imu_window_ms": [-args.imu_before_ms, args.imu_after_ms],
-        "time_basis": "LiDAR and serial host UTC; RTK GNSS time and IMU device time are retained for clock-model refinement",
-        "imu_orientation_warning": "IMU values are in the raw IMU sensor frame; no LiDAR/body extrinsic is applied",
-    }
-    (args.out / "dataset_summary.json").write_text(json.dumps(summary, ensure_ascii=False, indent=2), encoding="utf-8")
-    print(json.dumps(summary, ensure_ascii=False, indent=2))
-    return 0
-
-
-if __name__ == "__main__":
-    raise SystemExit(main())
diff --git a/LiDAR_RTK_Direct_Calibration/tools/frontlidar_dlog_export.py b/LiDAR_RTK_Direct_Calibration/tools/frontlidar_dlog_export.py
deleted file mode 100644
index 9bfd2fa..0000000
--- a/LiDAR_RTK_Direct_Calibration/tools/frontlidar_dlog_export.py
+++ /dev/null
@@ -1,1963 +0,0 @@
-#!/usr/bin/env python3
-"""Export Medulla DObject lidar + RTK recordings to sharded NumPy NPZ / pickle.
-
-The default NPZ path uses only the Python standard library; NumPy is required
-only when consuming the exported files, not while exporting them.
-"""
-
-from __future__ import annotations
-
-import argparse
-import array
-import bisect
-import csv
-import io
-import json
-import math
-import os
-import pickle
-import re
-import struct
-import sys
-import time
-import zipfile
-from contextlib import nullcontext
-from dataclasses import asdict, dataclass
-from datetime import datetime, timedelta, timezone
-from pathlib import Path
-from typing import BinaryIO, Iterable, Iterator, Sequence
-
-
-RECORD_RE = re.compile(
-    r"^\[(?P<log_time>[^]]+)\].*?DObject `(?P<name>[^`]+)` post "
-    r"len=(?P<len>\d+)B, id:(?P<id>[0-9A-Fa-f]+), tic:(?P<tic>\d+), "
-    r"@(?P<file>[^:]+):(?P<offset>\d+)"
-)
-GPS_TEXT_RE = re.compile(
-    r"^\[(?P<log_time>[^]]+)\].*?\$GPS-POST-Z>text\)>(?P<body>.+)$"
-)
-POINT_STRUCT = struct.Struct("<5f")
-DOTNET_UNIX_EPOCH_TICKS = 621355968000000000
-TICKS_PER_SECOND = 10_000_000
-TICKS_PER_DAY = 864_000_000_000
-NS_PER_TICK = 100
-FORMAT_VERSION = "medulla-lidar3d-rtk-v2"
-RTK_OBJECT_NAMES = ("GPS-POST-Z", "rtk", "GPS-POST")
-
-
-@dataclass(frozen=True)
-class RecordRef:
-    sequence: int
-    object_name: str
-    log_time: str
-    source_log: str
-    source_dorec: str
-    source_offset: int
-    payload_length: int
-    log_record_id: str
-    dotnet_ticks: int
-
-
-@dataclass
-class RtkSample:
-    index: int
-    source: str
-    object_name: str
-    dotnet_ticks: int
-    timestamp_iso_local: str
-    unix_time_ns: int
-    log_time: str
-    record_id: str
-    source_log: str
-    source_dorec: str
-    source_offset: int
-    payload_length: int
-    counter: int | None = None
-    lat: float | None = None
-    lon: float | None = None
-    alt_m: float | None = None
-    raw_heading_deg: float | None = None
-    vehicle_heading_deg: float | None = None
-    fix: int | None = None
-    sat: int | None = None
-    position_valid: bool | None = None
-    heading_valid: bool | None = None
-    heading_solution: str | None = None
-    position_time: str | None = None
-    heading_time: str | None = None
-    last_line: str | None = None
-    device_name: str | None = None
-    device_stamp_hex: str | None = None
-    raw_text: str | None = None
-    parse_error: str | None = None
-
-
-def parse_args() -> argparse.Namespace:
-    parser = argparse.ArgumentParser(
-        description=(
-            "Export Medulla frontlidar dlog records with matched RTK/GPS-POST-Z "
-            "to per-frame NPZ or pickle files."
-        )
-    )
-    parser.add_argument("--dlog", required=True, help="Directory containing dobject/ and dobject_recording/.")
-    parser.add_argument("--out", required=True, help="Output dataset directory.")
-    parser.add_argument("--object", default="frontlidar", help="Lidar DObject name; default: frontlidar.")
-    parser.add_argument("--format", choices=("npz", "pickle"), default="npz")
-    parser.add_argument("--timezone", default="+08:00", help="Fixed offset used to interpret DateTime.Now.Ticks.")
-    parser.add_argument("--stride", type=int, default=1, help="Export every Nth lidar frame.")
-    parser.add_argument("--max-frames", type=int, default=0, help="0 exports all selected frames.")
-    parser.add_argument("--resume", action="store_true", help="Keep already exported frame files.")
-    parser.add_argument("--compress", action="store_true", help="Use ZIP deflate level 1 for NPZ files.")
-    parser.add_argument(
-        "--include-xyz",
-        choices=("none", "sensor", "cart", "both"),
-        default="none",
-        help="Optionally generate XYZ arrays. Raw N x 5 data is always exported.",
-    )
-    parser.add_argument("--x", type=float, default=736.0, help="Lidar X in vehicle frame, mm.")
-    parser.add_argument("--y", type=float, default=0.0, help="Lidar Y in vehicle frame, mm.")
-    parser.add_argument("--z", type=float, default=0.0, help="Lidar Z in vehicle frame, mm.")
-    parser.add_argument("--yaw", type=float, default=0.0, help="Yaw in degrees.")
-    parser.add_argument("--pitch", type=float, default=0.0, help="Pitch in degrees.")
-    parser.add_argument("--roll", type=float, default=0.0, help="Roll in degrees.")
-    parser.add_argument(
-        "--rtk-max-dt-ms",
-        type=float,
-        default=1000.0,
-        help=(
-            "Fail rtk_time_alignment when an interior frame's nearest |dt| exceeds this many "
-            "milliseconds. Edge frames before the first / after the last RTK are reported "
-            "separately and do not fail the check."
-        ),
-    )
-    parser.add_argument(
-        "--skip-rtk",
-        action="store_true",
-        help="Export lidar only (no per-frame RTK matching).",
-    )
-    parser.add_argument(
-        "--rtk-sidecars",
-        action="store_true",
-        help=(
-            "Also write rtk/ sidecars (gps_post_z / rtk_binary / gps_post / text). "
-            "Default is off; per-frame NPZ still embeds matched RTK fields."
-        ),
-    )
-    parser.add_argument(
-        "--write-reports",
-        action="store_true",
-        help=(
-            "Write audit files under reports/ (metadata.json, manifest.csv, "
-            "rtk_match.csv, validation_report.json). Default package only has "
-            "frames/ and README.md."
-        ),
-    )
-    args = parser.parse_args()
-    if args.stride < 1:
-        parser.error("--stride must be >= 1")
-    if args.max_frames < 0:
-        parser.error("--max-frames must be >= 0")
-    if args.rtk_max_dt_ms < 0:
-        parser.error("--rtk-max-dt-ms must be >= 0")
-    if args.skip_rtk and args.rtk_sidecars:
-        parser.error("--rtk-sidecars cannot be used with --skip-rtk")
-    parse_timezone(args.timezone)
-    return args
-
-
-def resolve_dlog_root(value: str) -> Path:
-    root = Path(value).expanduser().resolve()
-    if (root / "dobject").is_dir() and (root / "dobject_recording").is_dir():
-        return root
-    child = root / "dlog"
-    if (child / "dobject").is_dir() and (child / "dobject_recording").is_dir():
-        return child
-    raise FileNotFoundError(f"{root} does not contain dobject and dobject_recording")
-
-
-def parse_timezone(text: str) -> timezone:
-    match = re.fullmatch(r"([+-])(\d{2}):(\d{2})", text.strip())
-    if not match:
-        raise ValueError(f"invalid timezone offset: {text!r}")
-    minutes = int(match.group(2)) * 60 + int(match.group(3))
-    if match.group(1) == "-":
-        minutes = -minutes
-    return timezone(timedelta(minutes=minutes))
-
-
-def timezone_minutes(tz: timezone) -> int:
-    return int(tz.utcoffset(None).total_seconds() // 60)
-
-
-def dotnet_ticks_to_values(ticks: int, tz: timezone) -> tuple[str, int]:
-    days, remainder = divmod(ticks, TICKS_PER_DAY)
-    seconds, subsecond_ticks = divmod(remainder, TICKS_PER_SECOND)
-    local_dt = datetime(1, 1, 1) + timedelta(days=days, seconds=seconds)
-    fraction = f"{subsecond_ticks:07d}"
-    offset = tz.utcoffset(None)
-    sign = "+" if offset >= timedelta(0) else "-"
-    total_minutes = abs(int(offset.total_seconds() // 60))
-    iso = f"{local_dt:%Y-%m-%dT%H:%M:%S}.{fraction}{sign}{total_minutes // 60:02d}:{total_minutes % 60:02d}"
-    offset_ticks = int(offset.total_seconds()) * TICKS_PER_SECOND
-    unix_ns = (ticks - DOTNET_UNIX_EPOCH_TICKS - offset_ticks) * NS_PER_TICK
-    return iso, unix_ns
-
-
-def discover_records(dlog_root: Path, object_name: str) -> list[RecordRef]:
-    pending: list[tuple[str, str, str, int, int, str, int, str]] = []
-    for log_path in sorted((dlog_root / "dobject").rglob("*.log")):
-        relative_log = log_path.relative_to(dlog_root).as_posix()
-        with log_path.open("r", encoding="utf-8", errors="replace") as stream:
-            for line in stream:
-                match = RECORD_RE.search(line)
-                if not match or match.group("name").casefold() != object_name.casefold():
-                    continue
-                pending.append(
-                    (
-                        match.group("name"),
-                        match.group("log_time"),
-                        relative_log,
-                        int(match.group("offset")),
-                        int(match.group("len")),
-                        match.group("id").upper(),
-                        int(match.group("tic")),
-                        match.group("file"),
-                    )
-                )
-    pending.sort(key=lambda item: (item[6], item[7].casefold(), item[3]))
-    seen: set[tuple[str, int, int]] = set()
-    records: list[RecordRef] = []
-    for item in pending:
-        key = (item[7].casefold(), item[3], item[6])
-        if key in seen:
-            continue
-        seen.add(key)
-        records.append(
-            RecordRef(
-                sequence=len(records),
-                object_name=item[0],
-                log_time=item[1],
-                source_log=item[2],
-                source_dorec=item[7],
-                source_offset=item[3],
-                payload_length=item[4],
-                log_record_id=item[5],
-                dotnet_ticks=item[6],
-            )
-        )
-    return records
-
-
-def index_dorec_files(dlog_root: Path) -> dict[str, list[Path]]:
-    result: dict[str, list[Path]] = {}
-    for path in (dlog_root / "dobject_recording").rglob("*.dorec"):
-        result.setdefault(path.name.casefold(), []).append(path)
-    return result
-
-
-def choose_dorec(index: dict[str, list[Path]], name: str) -> Path:
-    matches = index.get(Path(name).name.casefold(), [])
-    if not matches:
-        raise FileNotFoundError(f"missing recording file: {name}")
-    if len(matches) > 1:
-        raise RuntimeError(f"ambiguous recording file {name}: {matches}")
-    return matches[0]
-
-
-def read_exact(stream: BinaryIO, size: int) -> bytes:
-    data = stream.read(size)
-    if len(data) != size:
-        raise EOFError(f"expected {size} bytes, got {len(data)}")
-    return data
-
-
-def read_record(path: Path, record: RecordRef) -> tuple[dict[str, object], bytes]:
-    with path.open("rb") as stream:
-        stream.seek(record.source_offset)
-        name_length = read_exact(stream, 1)[0]
-        name = read_exact(stream, name_length).decode("ascii")
-        ticks = struct.unpack("<q", read_exact(stream, 8))[0]
-        id_length = read_exact(stream, 1)[0]
-        id_bytes = read_exact(stream, id_length)
-        payload_length = struct.unpack("<i", read_exact(stream, 4))[0]
-        payload = read_exact(stream, payload_length)
-
-    try:
-        record_id = id_bytes.decode("ascii")
-    except UnicodeDecodeError:
-        record_id = id_bytes.hex().upper()
-    if name != record.object_name:
-        raise ValueError(f"name mismatch: log={record.object_name}, dorec={name}")
-    if ticks != record.dotnet_ticks:
-        raise ValueError(f"tick mismatch: log={record.dotnet_ticks}, dorec={ticks}")
-    if payload_length != record.payload_length:
-        raise ValueError(f"payload mismatch: log={record.payload_length}, dorec={payload_length}")
-    if record_id.upper() != record.log_record_id.upper():
-        raise ValueError(f"record id mismatch: log={record.log_record_id}, dorec={record_id}")
-    return {
-        "record_id": record_id,
-        "record_id_bytes_hex": id_bytes.hex().upper(),
-        "payload_length": payload_length,
-    }, payload
-
-
-def parse_lidar_payload(payload: bytes) -> tuple[int, int, bytes]:
-    if len(payload) < 8:
-        raise ValueError(f"payload too short: {len(payload)}")
-    frame_counter, point_count = struct.unpack_from("<ii", payload, 0)
-    if point_count < 0:
-        raise ValueError(f"negative point count: {point_count}")
-    expected = 8 + point_count * POINT_STRUCT.size
-    if expected != len(payload):
-        raise ValueError(f"lidar payload length mismatch: expected={expected}, actual={len(payload)}")
-    return frame_counter, point_count, payload[8:]
-
-
-def read_len_prefixed_ascii(data: bytes, pos: int) -> tuple[str, int]:
-    if pos >= len(data):
-        raise ValueError("truncated length-prefixed string")
-    length = data[pos]
-    pos += 1
-    end = pos + length
-    if end > len(data):
-        raise ValueError("truncated length-prefixed string body")
-    return data[pos:end].decode("ascii", errors="replace"), end
-
-
-def parse_bool_text(value: str) -> bool | None:
-    lowered = value.strip().casefold()
-    if lowered in ("true", "1", "yes"):
-        return True
-    if lowered in ("false", "0", "no"):
-        return False
-    return None
-
-
-def parse_kv_payload(text: str, separators: Sequence[str] = ("=", ":")) -> dict[str, str]:
-    result: dict[str, str] = {}
-    for part in text.replace("\r", "").replace("\n", ",").split(","):
-        part = part.strip()
-        if not part:
-            continue
-        key = value = None
-        for sep in separators:
-            if sep in part:
-                key, value = part.split(sep, 1)
-                break
-        if key is None or value is None:
-            continue
-        result[key.strip()] = value.strip()
-    return result
-
-
-def coerce_int(value: str | None) -> int | None:
-    if value is None or value == "":
-        return None
-    try:
-        return int(float(value))
-    except ValueError:
-        return None
-
-
-def coerce_float(value: str | None) -> float | None:
-    if value is None or value == "":
-        return None
-    try:
-        return float(value)
-    except ValueError:
-        return None
-
-
-def parse_gps_post_z_text(text: str) -> dict[str, object]:
-    fields = parse_kv_payload(text, separators=("=", ":"))
-    alt = fields.get("alt", fields.get("h"))
-    vehicle_heading = fields.get("vehicleHeading", fields.get("th"))
-    return {
-        "counter": coerce_int(fields.get("counter")),
-        "lat": coerce_float(fields.get("lat")),
-        "lon": coerce_float(fields.get("lon")),
-        "alt_m": coerce_float(alt),
-        "raw_heading_deg": coerce_float(fields.get("rawHeading")),
-        "vehicle_heading_deg": coerce_float(vehicle_heading),
-        "fix": coerce_int(fields.get("fix")),
-        "sat": coerce_int(fields.get("sat")),
-        "position_valid": parse_bool_text(fields.get("positionValid", "")),
-        "heading_valid": parse_bool_text(fields.get("headingValid", "")),
-        "heading_solution": fields.get("headingSolution"),
-        "position_time": fields.get("positionTime"),
-        "heading_time": fields.get("headingTime"),
-        "last_line": fields.get("lastLine"),
-        "time_field": fields.get("time"),
-        "raw_fields": fields,
-    }
-
-
-def parse_rtk_binary_payload(payload: bytes) -> dict[str, object]:
-    pos = 0
-    device_name, pos = read_len_prefixed_ascii(payload, pos)
-    version, counter, unknown0 = struct.unpack_from("<iii", payload, pos)
-    pos += 12
-    device_stamp = payload[pos : pos + 8]
-    pos += 8
-    position_time, pos = read_len_prefixed_ascii(payload, pos)
-    heading_time, pos = read_len_prefixed_ascii(payload, pos)
-    lat, lon, alt, reserved0, reserved1 = struct.unpack_from("<ddddd", payload, pos)
-    pos += 40
-    fix, sat = struct.unpack_from("<ii", payload, pos)
-    pos += 8
-    if pos >= len(payload):
-        raise ValueError("rtk payload truncated before validity flags")
-    position_valid = bool(payload[pos])
-    pos += 1
-    raw_heading, vehicle_heading = struct.unpack_from("<dd", payload, pos)
-    pos += 16
-    if pos >= len(payload):
-        raise ValueError("rtk payload truncated before heading validity")
-    heading_valid = bool(payload[pos])
-    pos += 1
-    heading_solution, pos = read_len_prefixed_ascii(payload, pos)
-    has_nmea = bool(payload[pos]) if pos < len(payload) else False
-    if pos < len(payload):
-        pos += 1
-    last_line = None
-    if has_nmea and pos < len(payload):
-        last_line, pos = read_len_prefixed_ascii(payload, pos)
-    return {
-        "device_name": device_name,
-        "version": version,
-        "counter": counter,
-        "unknown0": unknown0,
-        "device_stamp_hex": device_stamp.hex().upper(),
-        "position_time": position_time,
-        "heading_time": heading_time,
-        "lat": lat,
-        "lon": lon,
-        "alt_m": alt,
-        "reserved0": reserved0,
-        "reserved1": reserved1,
-        "fix": fix,
-        "sat": sat,
-        "position_valid": position_valid,
-        "raw_heading_deg": raw_heading,
-        "vehicle_heading_deg": vehicle_heading,
-        "heading_valid": heading_valid,
-        "heading_solution": heading_solution,
-        "last_line": last_line,
-        "bytes_consumed": pos,
-        "payload_length": len(payload),
-    }
-
-
-def parse_gps_post_payload(payload: bytes) -> dict[str, object]:
-    pos = 0
-    name, pos = read_len_prefixed_ascii(payload, pos)
-    if pos + 20 > len(payload):
-        raise ValueError("GPS-POST payload too short")
-    counter, unknown0 = struct.unpack_from("<ii", payload, pos)
-    pos += 8
-    flags = payload[pos : pos + 4]
-    pos += 4
-    stamp = payload[pos : pos + 8]
-    pos += 8
-    floats = []
-    while pos + 4 <= len(payload):
-        floats.append(struct.unpack_from("<f", payload, pos)[0])
-        pos += 4
-    return {
-        "device_name": name,
-        "counter": counter,
-        "unknown0": unknown0,
-        "flags_hex": flags.hex().upper(),
-        "device_stamp_hex": stamp.hex().upper(),
-        "floats_f32": floats,
-        "payload_hex": payload.hex().upper(),
-    }
-
-
-def rotation_matrix(yaw_deg: float, pitch_deg: float, roll_deg: float) -> tuple[float, ...]:
-    yaw, pitch, roll = map(math.radians, (yaw_deg, pitch_deg, roll_deg))
-    cy, sy = math.cos(yaw), math.sin(yaw)
-    cp, sp = math.cos(pitch), math.sin(pitch)
-    cr, sr = math.cos(roll), math.sin(roll)
-    return (
-        cy * cp,
-        -sy * cr + cy * sp * sr,
-        sy * sr + cy * sp * cr,
-        sy * cp,
-        cy * cr + sy * sp * sr,
-        -cy * sr + sy * sp * cr,
-        -sp,
-        cp * sr,
-        cp * cr,
-    )
-
-
-def generate_xyz(
-    raw_points: bytes,
-    mode: str,
-    translation: tuple[float, float, float],
-    rotation: tuple[float, ...],
-) -> tuple[bytes | None, bytes | None]:
-    need_sensor = mode in ("sensor", "both")
-    need_cart = mode in ("cart", "both")
-    sensor = array.array("f") if need_sensor else None
-    cart = array.array("f") if need_cart else None
-    tx, ty, tz = translation
-    r = rotation
-    for distance, azimuth, altitude, _intensity, _progression in POINT_STRUCT.iter_unpack(raw_points):
-        alt = math.radians(altitude)
-        azi = math.radians(azimuth)
-        cos_alt = math.cos(alt)
-        sx = distance * cos_alt * math.cos(azi)
-        sy = distance * cos_alt * math.sin(azi)
-        sz = distance * math.sin(alt)
-        if sensor is not None:
-            sensor.extend((sx, sy, sz))
-        if cart is not None:
-            cart.extend(
-                (
-                    r[0] * sx + r[1] * sy + r[2] * sz + tx,
-                    r[3] * sx + r[4] * sy + r[5] * sz + ty,
-                    r[6] * sx + r[7] * sy + r[8] * sz + tz,
-                )
-            )
-    if sys.byteorder != "little":
-        if sensor is not None:
-            sensor.byteswap()
-        if cart is not None:
-            cart.byteswap()
-    return (sensor.tobytes() if sensor is not None else None, cart.tobytes() if cart is not None else None)
-
-
-def numpy_header(descr: str, shape: Sequence[int]) -> bytes:
-    shape_text = "(" + ", ".join(str(value) for value in shape)
-    if len(shape) == 1:
-        shape_text += ","
-    shape_text += ")"
-    header = f"{{'descr': '{descr}', 'fortran_order': False, 'shape': {shape_text}, }}"
-    encoded = header.encode("latin-1")
-    padding = (-((10 + len(encoded) + 1) % 16)) % 16
-    encoded += b" " * padding + b"\n"
-    if len(encoded) > 65535:
-        raise ValueError("NPY v1 header is too long")
-    return b"\x93NUMPY\x01\x00" + struct.pack("<H", len(encoded)) + encoded
-
-
-def write_npy_entry(
-    archive: zipfile.ZipFile,
-    name: str,
-    descr: str,
-    shape: Sequence[int],
-    data: bytes,
-) -> None:
-    with archive.open(name + ".npy", "w", force_zip64=True) as entry:
-        entry.write(numpy_header(descr, shape))
-        entry.write(data)
-
-
-def scalar_bytes(fmt: str, value: int | float) -> bytes:
-    return struct.pack(fmt, value)
-
-
-def open_npz_writer(path: Path, compress: bool) -> zipfile.ZipFile:
-    compression = zipfile.ZIP_DEFLATED if compress else zipfile.ZIP_STORED
-    kwargs: dict[str, object] = {"compression": compression, "allowZip64": True}
-    if compress:
-        kwargs["compresslevel"] = 1
-    return zipfile.ZipFile(path, "w", **kwargs)
-
-
-def pack_f64_array(values: Sequence[float]) -> bytes:
-    data = array.array("d", values)
-    if sys.byteorder != "little":
-        data.byteswap()
-    return data.tobytes()
-
-
-def pack_i8_array(values: Sequence[int]) -> bytes:
-    data = array.array("q", values)
-    if sys.byteorder != "little":
-        data.byteswap()
-    return data.tobytes()
-
-
-def pack_i4_array(values: Sequence[int]) -> bytes:
-    data = array.array("i", values)
-    if sys.byteorder != "little":
-        data.byteswap()
-    return data.tobytes()
-
-
-def pack_u1_bools(values: Sequence[bool | None]) -> bytes:
-    return bytes(1 if value else 0 for value in values)
-
-
-def export_npz(
-    path: Path,
-    metadata: dict[str, object],
-    raw_points: bytes,
-    point_count: int,
-    xyz_sensor: bytes | None,
-    xyz_cart: bytes | None,
-    compress: bool,
-    rtk_arrays: dict[str, tuple[str, Sequence[int], bytes]] | None = None,
-) -> None:
-    temp = path.with_suffix(path.suffix + ".tmp")
-    with open_npz_writer(temp, compress) as archive:
-        write_npy_entry(archive, "points_raw", "<f4", (point_count, 5), raw_points)
-        write_npy_entry(archive, "frame_counter", "<i4", (1,), scalar_bytes("<i", metadata["frame_counter"]))
-        write_npy_entry(archive, "point_count", "<i4", (1,), scalar_bytes("<i", point_count))
-        write_npy_entry(archive, "dotnet_ticks", "<i8", (1,), scalar_bytes("<q", metadata["dotnet_ticks"]))
-        write_npy_entry(archive, "unix_time_ns", "<i8", (1,), scalar_bytes("<q", metadata["unix_time_ns"]))
-        write_npy_entry(archive, "source_offset", "<i8", (1,), scalar_bytes("<q", metadata["source_offset"]))
-        write_npy_entry(archive, "payload_length", "<i4", (1,), scalar_bytes("<i", metadata["payload_length"]))
-        metadata_bytes = json.dumps(metadata, ensure_ascii=False, separators=(",", ":")).encode("utf-8")
-        write_npy_entry(archive, "metadata_json_utf8", "|u1", (len(metadata_bytes),), metadata_bytes)
-        if xyz_sensor is not None:
-            write_npy_entry(archive, "xyz_sensor_mm", "<f4", (point_count, 3), xyz_sensor)
-        if xyz_cart is not None:
-            write_npy_entry(archive, "xyz_cart_mm", "<f4", (point_count, 3), xyz_cart)
-        if rtk_arrays:
-            for name, (descr, shape, data) in rtk_arrays.items():
-                write_npy_entry(archive, name, descr, shape, data)
-    os.replace(temp, path)
-
-
-def export_pickle(
-    path: Path,
-    metadata: dict[str, object],
-    raw_points: bytes,
-    point_count: int,
-    xyz_sensor: bytes | None,
-    xyz_cart: bytes | None,
-) -> None:
-    points = array.array("f")
-    points.frombytes(raw_points)
-    if sys.byteorder != "little":
-        points.byteswap()
-    frame: dict[str, object] = {
-        "metadata": metadata,
-        "point_columns": ("d_mm", "azimuth_deg", "altitude_deg", "intensity", "progression"),
-        "points_raw_flat_f32": points,
-        "points_raw_shape": (point_count, 5),
-    }
-    for key, raw in (("xyz_sensor_mm_flat_f32", xyz_sensor), ("xyz_cart_mm_flat_f32", xyz_cart)):
-        if raw is not None:
-            values = array.array("f")
-            values.frombytes(raw)
-            if sys.byteorder != "little":
-                values.byteswap()
-            frame[key] = values
-            frame[key.replace("_flat_f32", "_shape")] = (point_count, 3)
-    temp = path.with_suffix(path.suffix + ".tmp")
-    with temp.open("wb") as stream:
-        pickle.dump(frame, stream, protocol=5)
-    os.replace(temp, path)
-
-
-def frame_filename(record: RecordRef, frame_counter: int, extension: str) -> str:
-    return f"{record.object_name}_{record.sequence:06d}_{record.dotnet_ticks}_frame{frame_counter:010d}.{extension}"
-
-
-def manifest_fields(include_rtk: bool) -> list[str]:
-    fields = [
-        "sequence",
-        "status",
-        "object_name",
-        "dotnet_ticks",
-        "timestamp_iso_local",
-        "unix_time_ns",
-        "log_time",
-        "record_id",
-        "record_id_bytes_hex",
-        "frame_counter",
-        "point_count",
-        "payload_length",
-        "source_log",
-        "source_dorec",
-        "source_offset",
-        "output_file",
-        "error",
-    ]
-    if include_rtk:
-        fields.extend(
-            [
-                "rtk_matched",
-                "rtk_nearest_index",
-                "rtk_prev_index",
-                "rtk_next_index",
-                "rtk_dt_ns",
-                "rtk_prev_dt_ns",
-                "rtk_next_dt_ns",
-                "rtk_lat",
-                "rtk_lon",
-                "rtk_alt_m",
-                "rtk_vehicle_heading_deg",
-                "rtk_raw_heading_deg",
-                "rtk_fix",
-                "rtk_sat",
-                "rtk_position_valid",
-                "rtk_heading_valid",
-                "rtk_heading_solution",
-            ]
-        )
-    return fields
-
-
-def nan_if_none(value: float | None) -> float:
-    return float("nan") if value is None else float(value)
-
-
-def int_or_sentinel(value: int | None, sentinel: int = -1) -> int:
-    return sentinel if value is None else int(value)
-
-
-def bool_or_false(value: bool | None) -> bool:
-    return bool(value)
-
-
-def sample_to_public_dict(sample: RtkSample) -> dict[str, object]:
-    data = asdict(sample)
-    return data
-
-
-def write_jsonl(path: Path, rows: Iterable[dict[str, object]]) -> int:
-    count = 0
-    with path.open("w", encoding="utf-8") as stream:
-        for row in rows:
-            stream.write(json.dumps(row, ensure_ascii=False, separators=(",", ":")))
-            stream.write("\n")
-            count += 1
-    return count
-
-
-def write_csv_rows(path: Path, fieldnames: Sequence[str], rows: Iterable[dict[str, object]]) -> int:
-    count = 0
-    with path.open("w", newline="", encoding="utf-8-sig") as stream:
-        writer = csv.DictWriter(stream, fieldnames=list(fieldnames), extrasaction="ignore")
-        writer.writeheader()
-        for row in rows:
-            writer.writerow({key: row.get(key, "") for key in fieldnames})
-            count += 1
-    return count
-
-
-def export_rtk_table_npz(path: Path, samples: Sequence[RtkSample], compress: bool) -> None:
-    n = len(samples)
-    temp = path.with_suffix(path.suffix + ".tmp")
-    with open_npz_writer(temp, compress) as archive:
-        write_npy_entry(archive, "index", "<i4", (n,), pack_i4_array([s.index for s in samples]))
-        write_npy_entry(archive, "dotnet_ticks", "<i8", (n,), pack_i8_array([s.dotnet_ticks for s in samples]))
-        write_npy_entry(archive, "unix_time_ns", "<i8", (n,), pack_i8_array([s.unix_time_ns for s in samples]))
-        write_npy_entry(archive, "counter", "<i4", (n,), pack_i4_array([int_or_sentinel(s.counter) for s in samples]))
-        write_npy_entry(archive, "lat", "<f8", (n,), pack_f64_array([nan_if_none(s.lat) for s in samples]))
-        write_npy_entry(archive, "lon", "<f8", (n,), pack_f64_array([nan_if_none(s.lon) for s in samples]))
-        write_npy_entry(archive, "alt_m", "<f8", (n,), pack_f64_array([nan_if_none(s.alt_m) for s in samples]))
-        write_npy_entry(
-            archive,
-            "raw_heading_deg",
-            "<f8",
-            (n,),
-            pack_f64_array([nan_if_none(s.raw_heading_deg) for s in samples]),
-        )
-        write_npy_entry(
-            archive,
-            "vehicle_heading_deg",
-            "<f8",
-            (n,),
-            pack_f64_array([nan_if_none(s.vehicle_heading_deg) for s in samples]),
-        )
-        write_npy_entry(archive, "fix", "<i4", (n,), pack_i4_array([int_or_sentinel(s.fix) for s in samples]))
-        write_npy_entry(archive, "sat", "<i4", (n,), pack_i4_array([int_or_sentinel(s.sat) for s in samples]))
-        write_npy_entry(
-            archive,
-            "position_valid",
-            "|u1",
-            (n,),
-            pack_u1_bools([s.position_valid for s in samples]),
-        )
-        write_npy_entry(
-            archive,
-            "heading_valid",
-            "|u1",
-            (n,),
-            pack_u1_bools([s.heading_valid for s in samples]),
-        )
-        write_npy_entry(
-            archive,
-            "source_offset",
-            "<i8",
-            (n,),
-            pack_i8_array([s.source_offset for s in samples]),
-        )
-        write_npy_entry(
-            archive,
-            "payload_length",
-            "<i4",
-            (n,),
-            pack_i4_array([s.payload_length for s in samples]),
-        )
-        meta_bytes = json.dumps(
-            [sample_to_public_dict(sample) for sample in samples],
-            ensure_ascii=False,
-            separators=(",", ":"),
-        ).encode("utf-8")
-        write_npy_entry(archive, "records_json_utf8", "|u1", (len(meta_bytes),), meta_bytes)
-    os.replace(temp, path)
-
-
-def load_gps_post_z_samples(
-    root: Path,
-    dorec_index: dict[str, list[Path]],
-    tz: timezone,
-    timezone_text: str,
-) -> tuple[list[RtkSample], dict[str, int]]:
-    records = discover_records(root, "GPS-POST-Z")
-    samples: list[RtkSample] = []
-    stats = {
-        "discovered": len(records),
-        "parsed_ok": 0,
-        "parse_errors": 0,
-        "read_errors": 0,
-    }
-    for record in records:
-        timestamp_iso, unix_ns = dotnet_ticks_to_values(record.dotnet_ticks, tz)
-        sample = RtkSample(
-            index=len(samples),
-            source="dobject",
-            object_name=record.object_name,
-            dotnet_ticks=record.dotnet_ticks,
-            timestamp_iso_local=timestamp_iso,
-            unix_time_ns=unix_ns,
-            log_time=record.log_time,
-            record_id=record.log_record_id,
-            source_log=record.source_log,
-            source_dorec=record.source_dorec,
-            source_offset=record.source_offset,
-            payload_length=record.payload_length,
-        )
-        try:
-            dorec_path = choose_dorec(dorec_index, record.source_dorec)
-            record_meta, payload = read_record(dorec_path, record)
-            sample.record_id = str(record_meta["record_id"])
-            text = payload.decode("utf-8", errors="replace")
-            sample.raw_text = text
-            parsed = parse_gps_post_z_text(text)
-            sample.counter = parsed["counter"]  # type: ignore[assignment]
-            sample.lat = parsed["lat"]  # type: ignore[assignment]
-            sample.lon = parsed["lon"]  # type: ignore[assignment]
-            sample.alt_m = parsed["alt_m"]  # type: ignore[assignment]
-            sample.raw_heading_deg = parsed["raw_heading_deg"]  # type: ignore[assignment]
-            sample.vehicle_heading_deg = parsed["vehicle_heading_deg"]  # type: ignore[assignment]
-            sample.fix = parsed["fix"]  # type: ignore[assignment]
-            sample.sat = parsed["sat"]  # type: ignore[assignment]
-            sample.position_valid = parsed["position_valid"]  # type: ignore[assignment]
-            sample.heading_valid = parsed["heading_valid"]  # type: ignore[assignment]
-            sample.heading_solution = parsed["heading_solution"]  # type: ignore[assignment]
-            sample.position_time = parsed["position_time"]  # type: ignore[assignment]
-            sample.heading_time = parsed["heading_time"]  # type: ignore[assignment]
-            sample.last_line = parsed["last_line"]  # type: ignore[assignment]
-            stats["parsed_ok"] += 1
-        except Exception as exc:
-            sample.parse_error = f"{type(exc).__name__}: {exc}"
-            if "read" in type(exc).__name__.casefold() or "mismatch" in str(exc).casefold():
-                stats["read_errors"] += 1
-            else:
-                stats["parse_errors"] += 1
-        samples.append(sample)
-    _ = timezone_text
-    return samples, stats
-
-
-def load_rtk_binary_samples(
-    root: Path,
-    dorec_index: dict[str, list[Path]],
-    tz: timezone,
-) -> tuple[list[RtkSample], dict[str, int]]:
-    records = discover_records(root, "rtk")
-    samples: list[RtkSample] = []
-    stats = {"discovered": len(records), "parsed_ok": 0, "parse_errors": 0, "read_errors": 0}
-    for record in records:
-        timestamp_iso, unix_ns = dotnet_ticks_to_values(record.dotnet_ticks, tz)
-        sample = RtkSample(
-            index=len(samples),
-            source="dobject",
-            object_name=record.object_name,
-            dotnet_ticks=record.dotnet_ticks,
-            timestamp_iso_local=timestamp_iso,
-            unix_time_ns=unix_ns,
-            log_time=record.log_time,
-            record_id=record.log_record_id,
-            source_log=record.source_log,
-            source_dorec=record.source_dorec,
-            source_offset=record.source_offset,
-            payload_length=record.payload_length,
-        )
-        try:
-            dorec_path = choose_dorec(dorec_index, record.source_dorec)
-            record_meta, payload = read_record(dorec_path, record)
-            sample.record_id = str(record_meta["record_id"])
-            parsed = parse_rtk_binary_payload(payload)
-            sample.device_name = str(parsed["device_name"])
-            sample.device_stamp_hex = str(parsed["device_stamp_hex"])
-            sample.counter = int(parsed["counter"])  # type: ignore[arg-type]
-            sample.lat = float(parsed["lat"])  # type: ignore[arg-type]
-            sample.lon = float(parsed["lon"])  # type: ignore[arg-type]
-            sample.alt_m = float(parsed["alt_m"])  # type: ignore[arg-type]
-            sample.raw_heading_deg = float(parsed["raw_heading_deg"])  # type: ignore[arg-type]
-            sample.vehicle_heading_deg = float(parsed["vehicle_heading_deg"])  # type: ignore[arg-type]
-            sample.fix = int(parsed["fix"])  # type: ignore[arg-type]
-            sample.sat = int(parsed["sat"])  # type: ignore[arg-type]
-            sample.position_valid = bool(parsed["position_valid"])
-            sample.heading_valid = bool(parsed["heading_valid"])
-            sample.heading_solution = str(parsed["heading_solution"])
-            sample.position_time = str(parsed["position_time"])
-            sample.heading_time = str(parsed["heading_time"])
-            sample.last_line = parsed["last_line"]  # type: ignore[assignment]
-            sample.raw_text = json.dumps(parsed, ensure_ascii=False, separators=(",", ":"))
-            stats["parsed_ok"] += 1
-        except Exception as exc:
-            sample.parse_error = f"{type(exc).__name__}: {exc}"
-            stats["parse_errors"] += 1
-        samples.append(sample)
-    return samples, stats
-
-
-def load_gps_post_samples(
-    root: Path,
-    dorec_index: dict[str, list[Path]],
-    tz: timezone,
-) -> tuple[list[dict[str, object]], dict[str, int]]:
-    records = discover_records(root, "GPS-POST")
-    rows: list[dict[str, object]] = []
-    stats = {"discovered": len(records), "parsed_ok": 0, "parse_errors": 0, "read_errors": 0}
-    for index, record in enumerate(records):
-        timestamp_iso, unix_ns = dotnet_ticks_to_values(record.dotnet_ticks, tz)
-        row: dict[str, object] = {
-            "index": index,
-            "object_name": record.object_name,
-            "dotnet_ticks": record.dotnet_ticks,
-            "timestamp_iso_local": timestamp_iso,
-            "unix_time_ns": unix_ns,
-            "log_time": record.log_time,
-            "record_id": record.log_record_id,
-            "source_log": record.source_log,
-            "source_dorec": record.source_dorec,
-            "source_offset": record.source_offset,
-            "payload_length": record.payload_length,
-            "parse_error": "",
-        }
-        try:
-            dorec_path = choose_dorec(dorec_index, record.source_dorec)
-            record_meta, payload = read_record(dorec_path, record)
-            row["record_id"] = record_meta["record_id"]
-            parsed = parse_gps_post_payload(payload)
-            row.update(parsed)
-            stats["parsed_ok"] += 1
-        except Exception as exc:
-            row["parse_error"] = f"{type(exc).__name__}: {exc}"
-            stats["parse_errors"] += 1
-        rows.append(row)
-    return rows, stats
-
-
-def load_gps_post_z_text_logs(root: Path) -> tuple[list[dict[str, object]], dict[str, int]]:
-    rows: list[dict[str, object]] = []
-    stats = {"files": 0, "lines": 0, "parsed_ok": 0, "parse_errors": 0}
-    text_root = root / "GPS-POST-Z"
-    if not text_root.is_dir():
-        return rows, stats
-    for log_path in sorted(text_root.rglob("*.log")):
-        stats["files"] += 1
-        relative = log_path.relative_to(root).as_posix()
-        with log_path.open("r", encoding="utf-8", errors="replace") as stream:
-            for line_no, line in enumerate(stream, start=1):
-                match = GPS_TEXT_RE.search(line)
-                if not match:
-                    continue
-                stats["lines"] += 1
-                body = match.group("body").strip()
-                row: dict[str, object] = {
-                    "index": len(rows),
-                    "source": "GPS-POST-Z-text-log",
-                    "source_log": relative,
-                    "line_no": line_no,
-                    "log_time": match.group("log_time"),
-                    "raw_text": body,
-                    "parse_error": "",
-                }
-                try:
-                    parsed = parse_gps_post_z_text(body)
-                    row.update(
-                        {
-                            "lat": parsed["lat"],
-                            "lon": parsed["lon"],
-                            "alt_m": parsed["alt_m"],
-                            "raw_heading_deg": parsed["raw_heading_deg"],
-                            "vehicle_heading_deg": parsed["vehicle_heading_deg"],
-                            "fix": parsed["fix"],
-                            "sat": parsed["sat"],
-                            "position_valid": parsed["position_valid"],
-                            "heading_valid": parsed["heading_valid"],
-                            "heading_solution": parsed["heading_solution"],
-                            "position_time": parsed["position_time"],
-                            "heading_time": parsed["heading_time"],
-                        }
-                    )
-                    stats["parsed_ok"] += 1
-                except Exception as exc:
-                    row["parse_error"] = f"{type(exc).__name__}: {exc}"
-                    stats["parse_errors"] += 1
-                rows.append(row)
-    return rows, stats
-
-
-def match_rtk(unix_time_ns: int, samples: Sequence[RtkSample]) -> dict[str, object]:
-    if not samples:
-        return {
-            "matched": False,
-            "nearest_index": -1,
-            "prev_index": -1,
-            "next_index": -1,
-            "dt_ns": None,
-            "prev_dt_ns": None,
-            "next_dt_ns": None,
-            "sample": None,
-        }
-    ticks = [sample.unix_time_ns for sample in samples]
-    pos = bisect.bisect_left(ticks, unix_time_ns)
-    if pos < len(samples) and ticks[pos] == unix_time_ns:
-        nearest = prev_index = next_index = pos
-    else:
-        candidates: list[int] = []
-        if pos < len(samples):
-            candidates.append(pos)
-        if pos > 0:
-            candidates.append(pos - 1)
-        nearest = min(candidates, key=lambda idx: (abs(ticks[idx] - unix_time_ns), idx))
-        prev_index = pos - 1 if pos > 0 else -1
-        next_index = pos if pos < len(samples) else -1
-    sample = samples[nearest]
-    prev_dt = None if prev_index < 0 else unix_time_ns - samples[prev_index].unix_time_ns
-    next_dt = None if next_index < 0 else samples[next_index].unix_time_ns - unix_time_ns
-    return {
-        "matched": True,
-        "nearest_index": nearest,
-        "prev_index": prev_index,
-        "next_index": next_index,
-        "dt_ns": unix_time_ns - sample.unix_time_ns,
-        "prev_dt_ns": prev_dt,
-        "next_dt_ns": next_dt,
-        "sample": sample,
-    }
-
-
-def rtk_frame_arrays(match: dict[str, object]) -> dict[str, tuple[str, Sequence[int], bytes]]:
-    sample: RtkSample | None = match["sample"]  # type: ignore[assignment]
-    return {
-        "rtk_nearest_index": ("<i4", (1,), scalar_bytes("<i", int(match["nearest_index"]))),
-        "rtk_prev_index": ("<i4", (1,), scalar_bytes("<i", int(match["prev_index"]))),
-        "rtk_next_index": ("<i4", (1,), scalar_bytes("<i", int(match["next_index"]))),
-        "rtk_dt_ns": (
-            "<i8",
-            (1,),
-            scalar_bytes("<q", 0 if match["dt_ns"] is None else int(match["dt_ns"])),
-        ),
-        "rtk_prev_dt_ns": (
-            "<i8",
-            (1,),
-            scalar_bytes("<q", 0 if match["prev_dt_ns"] is None else int(match["prev_dt_ns"])),
-        ),
-        "rtk_next_dt_ns": (
-            "<i8",
-            (1,),
-            scalar_bytes("<q", 0 if match["next_dt_ns"] is None else int(match["next_dt_ns"])),
-        ),
-        "rtk_lat": ("<f8", (1,), scalar_bytes("<d", nan_if_none(None if sample is None else sample.lat))),
-        "rtk_lon": ("<f8", (1,), scalar_bytes("<d", nan_if_none(None if sample is None else sample.lon))),
-        "rtk_alt_m": ("<f8", (1,), scalar_bytes("<d", nan_if_none(None if sample is None else sample.alt_m))),
-        "rtk_raw_heading_deg": (
-            "<f8",
-            (1,),
-            scalar_bytes("<d", nan_if_none(None if sample is None else sample.raw_heading_deg)),
-        ),
-        "rtk_vehicle_heading_deg": (
-            "<f8",
-            (1,),
-            scalar_bytes("<d", nan_if_none(None if sample is None else sample.vehicle_heading_deg)),
-        ),
-        "rtk_fix": ("<i4", (1,), scalar_bytes("<i", int_or_sentinel(None if sample is None else sample.fix))),
-        "rtk_sat": ("<i4", (1,), scalar_bytes("<i", int_or_sentinel(None if sample is None else sample.sat))),
-        "rtk_position_valid": (
-            "|u1",
-            (1,),
-            bytes((1 if sample and sample.position_valid else 0,)),
-        ),
-        "rtk_heading_valid": (
-            "|u1",
-            (1,),
-            bytes((1 if sample and sample.heading_valid else 0,)),
-        ),
-    }
-
-
-def export_rtk_sidecars(
-    output: Path,
-    compress: bool,
-    gps_post_z: Sequence[RtkSample],
-    rtk_binary: Sequence[RtkSample],
-    gps_post_rows: Sequence[dict[str, object]],
-    text_rows: Sequence[dict[str, object]],
-) -> dict[str, object]:
-    rtk_dir = output / "rtk"
-    rtk_dir.mkdir(exist_ok=True)
-    written: dict[str, object] = {"directory": "rtk"}
-
-    export_rtk_table_npz(rtk_dir / "gps_post_z.npz", gps_post_z, compress)
-    gps_dicts = [sample_to_public_dict(sample) for sample in gps_post_z]
-    write_jsonl(rtk_dir / "gps_post_z.jsonl", gps_dicts)
-    write_csv_rows(
-        rtk_dir / "gps_post_z.csv",
-        [
-            "index",
-            "dotnet_ticks",
-            "timestamp_iso_local",
-            "unix_time_ns",
-            "log_time",
-            "record_id",
-            "counter",
-            "lat",
-            "lon",
-            "alt_m",
-            "raw_heading_deg",
-            "vehicle_heading_deg",
-            "fix",
-            "sat",
-            "position_valid",
-            "heading_valid",
-            "heading_solution",
-            "position_time",
-            "heading_time",
-            "last_line",
-            "source_log",
-            "source_dorec",
-            "source_offset",
-            "payload_length",
-            "parse_error",
-            "raw_text",
-        ],
-        gps_dicts,
-    )
-    written["gps_post_z"] = {
-        "npz": "rtk/gps_post_z.npz",
-        "csv": "rtk/gps_post_z.csv",
-        "jsonl": "rtk/gps_post_z.jsonl",
-        "count": len(gps_post_z),
-    }
-
-    export_rtk_table_npz(rtk_dir / "rtk_binary.npz", rtk_binary, compress)
-    rtk_dicts = [sample_to_public_dict(sample) for sample in rtk_binary]
-    write_jsonl(rtk_dir / "rtk_binary.jsonl", rtk_dicts)
-    write_csv_rows(
-        rtk_dir / "rtk_binary.csv",
-        [
-            "index",
-            "dotnet_ticks",
-            "timestamp_iso_local",
-            "unix_time_ns",
-            "log_time",
-            "record_id",
-            "device_name",
-            "device_stamp_hex",
-            "counter",
-            "lat",
-            "lon",
-            "alt_m",
-            "raw_heading_deg",
-            "vehicle_heading_deg",
-            "fix",
-            "sat",
-            "position_valid",
-            "heading_valid",
-            "heading_solution",
-            "position_time",
-            "heading_time",
-            "last_line",
-            "source_log",
-            "source_dorec",
-            "source_offset",
-            "payload_length",
-            "parse_error",
-        ],
-        rtk_dicts,
-    )
-    written["rtk_binary"] = {
-        "npz": "rtk/rtk_binary.npz",
-        "csv": "rtk/rtk_binary.csv",
-        "jsonl": "rtk/rtk_binary.jsonl",
-        "count": len(rtk_binary),
-    }
-
-    write_jsonl(rtk_dir / "gps_post.jsonl", gps_post_rows)
-    write_csv_rows(
-        rtk_dir / "gps_post.csv",
-        [
-            "index",
-            "dotnet_ticks",
-            "timestamp_iso_local",
-            "unix_time_ns",
-            "log_time",
-            "record_id",
-            "device_name",
-            "counter",
-            "unknown0",
-            "flags_hex",
-            "device_stamp_hex",
-            "source_log",
-            "source_dorec",
-            "source_offset",
-            "payload_length",
-            "payload_hex",
-            "parse_error",
-        ],
-        gps_post_rows,
-    )
-    # Compact NPZ for GPS-POST counters / stamps only.
-    temp = (rtk_dir / "gps_post.npz").with_suffix(".npz.tmp")
-    with open_npz_writer(temp, compress) as archive:
-        n = len(gps_post_rows)
-        write_npy_entry(
-            archive,
-            "index",
-            "<i4",
-            (n,),
-            pack_i4_array([int(row["index"]) for row in gps_post_rows]),
-        )
-        write_npy_entry(
-            archive,
-            "dotnet_ticks",
-            "<i8",
-            (n,),
-            pack_i8_array([int(row["dotnet_ticks"]) for row in gps_post_rows]),
-        )
-        write_npy_entry(
-            archive,
-            "unix_time_ns",
-            "<i8",
-            (n,),
-            pack_i8_array([int(row["unix_time_ns"]) for row in gps_post_rows]),
-        )
-        write_npy_entry(
-            archive,
-            "counter",
-            "<i4",
-            (n,),
-            pack_i4_array([int(row.get("counter", -1) or -1) for row in gps_post_rows]),
-        )
-        meta_bytes = json.dumps(list(gps_post_rows), ensure_ascii=False, separators=(",", ":")).encode("utf-8")
-        write_npy_entry(archive, "records_json_utf8", "|u1", (len(meta_bytes),), meta_bytes)
-    os.replace(temp, rtk_dir / "gps_post.npz")
-    written["gps_post"] = {
-        "npz": "rtk/gps_post.npz",
-        "csv": "rtk/gps_post.csv",
-        "jsonl": "rtk/gps_post.jsonl",
-        "count": len(gps_post_rows),
-    }
-
-    write_jsonl(rtk_dir / "gps_post_z_text.jsonl", text_rows)
-    write_csv_rows(
-        rtk_dir / "gps_post_z_text.csv",
-        [
-            "index",
-            "source_log",
-            "line_no",
-            "log_time",
-            "lat",
-            "lon",
-            "alt_m",
-            "raw_heading_deg",
-            "vehicle_heading_deg",
-            "fix",
-            "sat",
-            "position_valid",
-            "heading_valid",
-            "heading_solution",
-            "position_time",
-            "heading_time",
-            "raw_text",
-            "parse_error",
-        ],
-        text_rows,
-    )
-    written["gps_post_z_text"] = {
-        "csv": "rtk/gps_post_z_text.csv",
-        "jsonl": "rtk/gps_post_z_text.jsonl",
-        "count": len(text_rows),
-    }
-    return written
-
-
-def build_validation_report(
-    *,
-    lidar_stats: dict[str, object],
-    gps_post_z_stats: dict[str, int],
-    rtk_binary_stats: dict[str, int],
-    gps_post_stats: dict[str, int],
-    text_stats: dict[str, int],
-    match_dts_ns: Sequence[int],
-    interior_dts_ns: Sequence[int],
-    edge_frames: int,
-    matched_frames: int,
-    unmatched_frames: int,
-    rtk_max_dt_ms: float,
-    rtk_sidecars: bool,
-) -> dict[str, object]:
-    abs_dts = [abs(value) for value in match_dts_ns]
-    abs_interior = [abs(value) for value in interior_dts_ns]
-    threshold_ns = rtk_max_dt_ms * 1_000_000.0
-    over_threshold = sum(1 for value in abs_interior if value > threshold_ns)
-    checks: list[dict[str, object]] = [
-        {
-            "name": "lidar_payload_length",
-            "ok": lidar_stats.get("frames_with_errors", 0) == 0,
-            "detail": "Each lidar payload must equal 8 + point_count * 20.",
-        },
-        {
-            "name": "gps_post_z_parse",
-            "ok": gps_post_z_stats.get("parse_errors", 0) == 0
-            and gps_post_z_stats.get("read_errors", 0) == 0,
-            "detail": "All GPS-POST-Z dobject payloads should parse.",
-        },
-        {
-            "name": "lidar_rtk_coverage",
-            "ok": unmatched_frames == 0,
-            "detail": "Every exported lidar frame should have a nearest GPS-POST-Z sample.",
-        },
-        {
-            "name": "rtk_time_alignment",
-            "ok": over_threshold == 0,
-            "detail": (
-                f"Interior frames (with both prev/next RTK) should have nearest |dt| "
-                f"<= {rtk_max_dt_ms} ms."
-            ),
-        },
-    ]
-    if rtk_sidecars:
-        checks.insert(
-            2,
-            {
-                "name": "rtk_binary_parse",
-                "ok": rtk_binary_stats.get("parse_errors", 0) == 0,
-                "detail": "All rtk binary payloads should parse as UNICORE_N4_RTK_V1.",
-            },
-        )
-    report = {
-        "format_version": FORMAT_VERSION,
-        "generated_at": datetime.now().astimezone().isoformat(),
-        "lidar": lidar_stats,
-        "rtk_sidecars": rtk_sidecars,
-        "rtk_sources": {
-            "GPS-POST-Z_dobject": gps_post_z_stats,
-            "rtk_dobject": rtk_binary_stats if rtk_sidecars else {"skipped": True},
-            "GPS-POST_dobject": gps_post_stats if rtk_sidecars else {"skipped": True},
-            "GPS-POST-Z_text_log": text_stats if rtk_sidecars else {"skipped": True},
-        },
-        "matching": {
-            "primary_source": "GPS-POST-Z",
-            "matched_frames": matched_frames,
-            "unmatched_frames": unmatched_frames,
-            "edge_frames_outside_rtk_span": edge_frames,
-            "rtk_max_dt_ms_threshold": rtk_max_dt_ms,
-            "interior_frames_over_threshold": over_threshold,
-            "dt_ns": {
-                "count": len(abs_dts),
-                "min": min(match_dts_ns) if match_dts_ns else None,
-                "max": max(match_dts_ns) if match_dts_ns else None,
-                "abs_min": min(abs_dts) if abs_dts else None,
-                "abs_max": max(abs_dts) if abs_dts else None,
-                "abs_mean": (sum(abs_dts) / len(abs_dts)) if abs_dts else None,
-            },
-            "interior_dt_ns": {
-                "count": len(abs_interior),
-                "abs_min": min(abs_interior) if abs_interior else None,
-                "abs_max": max(abs_interior) if abs_interior else None,
-                "abs_mean": (sum(abs_interior) / len(abs_interior)) if abs_interior else None,
-            },
-        },
-        "checks": checks,
-    }
-    report["ok"] = all(bool(check["ok"]) for check in checks)
-    return report
-
-
-def write_package_readme(
-    path: Path,
-    *,
-    format_version: str,
-    frame_count: int,
-    include_rtk: bool,
-    timezone_text: str,
-) -> None:
-    rtk_note = (
-        "每帧 NPZ 已嵌入最近 RTK：`rtk_lat` / `rtk_lon` / `rtk_alt_m` / "
-        "`rtk_vehicle_heading_deg` / `rtk_fix` / `rtk_sat` 等。\n"
-        if include_rtk
-        else "本包未嵌入 RTK（导出时使用了 `--skip-rtk`）。\n"
-    )
-    text = """# FrontLidar 数据集
-
-格式版本：`@@FORMAT_VERSION@@`  
-帧数：`@@FRAME_COUNT@@`  
-时区：`@@TIMEZONE@@`
-
-## 目录
-
-```text
-.
-  README.md          # 本说明
-  frames/            # 逐帧 NPZ
-    frontlidar_<seq>_<ticks>_frame<counter>.npz
-```
-
-直接打包本目录即可分发。
-
-## 依赖
-
-```powershell
-pip install numpy
-```
-
-## 快速读取
-
-```python
-import json
-from pathlib import Path
-import numpy as np
-
-root = Path(__file__).resolve().parent  # 或改成数据集路径
-frame_path = next(sorted((root / "frames").glob("*.npz")))
-
-with np.load(frame_path, allow_pickle=False) as f:
-    points = f["points_raw"]          # float32 (N, 5)
-    unix_ns = int(f["unix_time_ns"][0])
-    meta = json.loads(f["metadata_json_utf8"].tobytes().decode("utf-8"))
-
-    # 列: d_mm, azimuth_deg, altitude_deg, intensity, progression
-    d_mm, az, alt, intensity, prog = (points[:, i] for i in range(5))
-
-    # RTK（若导出时未 --skip-rtk）
-    if "rtk_lat" in f.files:
-        lat = float(f["rtk_lat"][0])
-        lon = float(f["rtk_lon"][0])
-        heading = float(f["rtk_vehicle_heading_deg"][0])
-        dt_ms = int(f["rtk_dt_ns"][0]) / 1e6
-        print(lat, lon, heading, dt_ms, meta.get("rtk", {}).get("heading_solution"))
-```
-
-@@RTK_NOTE@@
-## 点云列
-
-| 列 | 字段 | 单位 |
-|---:|---|---|
-| 0 | d_mm | mm |
-| 1 | azimuth_deg | ° |
-| 2 | altitude_deg | ° |
-| 3 | intensity | 设备定义 |
-| 4 | progression | 0–1 |
-
-极坐标转传感器 XYZ（mm）：
-
-```python
-az = np.deg2rad(points[:, 1])
-alt = np.deg2rad(points[:, 2])
-d = points[:, 0]
-xyz = np.column_stack((
-    d * np.cos(alt) * np.cos(az),
-    d * np.cos(alt) * np.sin(az),
-    d * np.sin(alt),
-)).astype(np.float32)
-```
-
-## 时间戳
-
-- `dotnet_ticks`：原始权威时间
-- `unix_time_ns`：按导出时区转换的 Unix 纳秒
-- 标量字段均为 shape `(1,)`，用 `[0]` 取出
-
-## 批量遍历
-
-```python
-for path in sorted((root / "frames").glob("*.npz")):
-    with np.load(path, allow_pickle=False) as f:
-        pts = f["points_raw"]
-        # ...
-```
-
-更多字段说明见导出仓库中的 `FRONTLIDAR_NPZ_READ.md`（若一并提供）。
-"""
-    text = (
-        text.replace("@@FORMAT_VERSION@@", format_version)
-        .replace("@@FRAME_COUNT@@", str(frame_count))
-        .replace("@@TIMEZONE@@", timezone_text)
-        .replace("@@RTK_NOTE@@", rtk_note)
-    )
-    path.write_text(text, encoding="utf-8")
-
-
-def export_dataset(args: argparse.Namespace) -> int:
-    started = time.time()
-    root = resolve_dlog_root(args.dlog)
-    output = Path(args.out).expanduser().resolve()
-    output.mkdir(parents=True, exist_ok=True)
-    frames_dir = output / "frames"
-    frames_dir.mkdir(exist_ok=True)
-    tz = parse_timezone(args.timezone)
-    records = discover_records(root, args.object)
-    selected = records[:: args.stride]
-    if args.max_frames:
-        selected = selected[: args.max_frames]
-    if not selected:
-        raise RuntimeError(f"no DObject records named {args.object!r} found under {root}")
-    dorec_index = index_dorec_files(root)
-    rotation = rotation_matrix(args.yaw, args.pitch, args.roll)
-    translation = (args.x, args.y, args.z)
-    extension = "npz" if args.format == "npz" else "pkl"
-    include_rtk = not args.skip_rtk
-    rtk_sidecars = bool(args.rtk_sidecars)
-
-    gps_post_z: list[RtkSample] = []
-    rtk_binary: list[RtkSample] = []
-    gps_post_rows: list[dict[str, object]] = []
-    text_rows: list[dict[str, object]] = []
-    gps_post_z_stats = {"discovered": 0, "parsed_ok": 0, "parse_errors": 0, "read_errors": 0}
-    rtk_binary_stats = {"discovered": 0, "parsed_ok": 0, "parse_errors": 0, "read_errors": 0}
-    gps_post_stats = {"discovered": 0, "parsed_ok": 0, "parse_errors": 0, "read_errors": 0}
-    text_stats = {"files": 0, "lines": 0, "parsed_ok": 0, "parse_errors": 0}
-    rtk_outputs: dict[str, object] = {}
-
-    if include_rtk:
-        print("Loading GPS-POST-Z for per-frame RTK matching...", flush=True)
-        gps_post_z, gps_post_z_stats = load_gps_post_z_samples(root, dorec_index, tz, args.timezone)
-        if rtk_sidecars:
-            print("Loading RTK sidecars...", flush=True)
-            rtk_binary, rtk_binary_stats = load_rtk_binary_samples(root, dorec_index, tz)
-            gps_post_rows, gps_post_stats = load_gps_post_samples(root, dorec_index, tz)
-            text_rows, text_stats = load_gps_post_z_text_logs(root)
-            rtk_outputs = export_rtk_sidecars(
-                output,
-                bool(args.compress and args.format == "npz"),
-                gps_post_z,
-                rtk_binary,
-                gps_post_rows,
-                text_rows,
-            )
-            print(
-                f"RTK loaded: GPS-POST-Z={len(gps_post_z)} rtk={len(rtk_binary)} "
-                f"GPS-POST={len(gps_post_rows)} text={len(text_rows)} (sidecars on)",
-                flush=True,
-            )
-        else:
-            print(
-                f"RTK loaded: GPS-POST-Z={len(gps_post_z)} (sidecars off; use --rtk-sidecars to write rtk/)",
-                flush=True,
-            )
-
-    write_reports = bool(args.write_reports)
-    reports_dir = output / "reports"
-    if write_reports:
-        reports_dir.mkdir(exist_ok=True)
-        manifest_tmp = reports_dir / "manifest.partial.csv"
-        manifest_final = reports_dir / "manifest.csv"
-        match_tmp = reports_dir / "rtk_match.partial.csv"
-        match_final = reports_dir / "rtk_match.csv"
-        manifest_stream_cm: object = manifest_tmp.open("w", newline="", encoding="utf-8-sig")
-        match_stream = (
-            match_tmp.open("w", newline="", encoding="utf-8-sig") if include_rtk else None
-        )
-    else:
-        manifest_tmp = manifest_final = match_tmp = match_final = None
-        manifest_stream_cm = nullcontext(io.StringIO())
-        match_stream = io.StringIO() if include_rtk else None
-
-    exported = skipped = resumed = total_points = 0
-    matched_frames = unmatched_frames = edge_frames = 0
-    match_dts_ns: list[int] = []
-    interior_dts_ns: list[int] = []
-    match_fieldnames = [
-        "sequence",
-        "lidar_unix_time_ns",
-        "lidar_dotnet_ticks",
-        "output_file",
-        "rtk_matched",
-        "rtk_nearest_index",
-        "rtk_prev_index",
-        "rtk_next_index",
-        "rtk_dt_ns",
-        "rtk_prev_dt_ns",
-        "rtk_next_dt_ns",
-        "rtk_dotnet_ticks",
-        "rtk_unix_time_ns",
-        "rtk_lat",
-        "rtk_lon",
-        "rtk_alt_m",
-        "rtk_raw_heading_deg",
-        "rtk_vehicle_heading_deg",
-        "rtk_fix",
-        "rtk_sat",
-        "rtk_position_valid",
-        "rtk_heading_valid",
-        "rtk_heading_solution",
-        "rtk_position_time",
-        "rtk_heading_time",
-        "rtk_last_line",
-        "rtk_source_dorec",
-        "rtk_source_offset",
-    ]
-
-    match_writer = csv.DictWriter(match_stream, fieldnames=match_fieldnames) if match_stream else None
-    if match_writer:
-        match_writer.writeheader()
-
-    with manifest_stream_cm as manifest_stream:
-        writer = csv.DictWriter(manifest_stream, fieldnames=manifest_fields(include_rtk))
-        writer.writeheader()
-        for selected_index, record in enumerate(selected):
-            row: dict[str, object] = {
-                "sequence": record.sequence,
-                "status": "error",
-                "object_name": record.object_name,
-                "dotnet_ticks": record.dotnet_ticks,
-                "timestamp_iso_local": "",
-                "unix_time_ns": "",
-                "log_time": record.log_time,
-                "record_id": record.log_record_id,
-                "record_id_bytes_hex": "",
-                "frame_counter": "",
-                "point_count": "",
-                "payload_length": record.payload_length,
-                "source_log": record.source_log,
-                "source_dorec": record.source_dorec,
-                "source_offset": record.source_offset,
-                "output_file": "",
-                "error": "",
-            }
-            if include_rtk:
-                row.update(
-                    {
-                        "rtk_matched": False,
-                        "rtk_nearest_index": -1,
-                        "rtk_prev_index": -1,
-                        "rtk_next_index": -1,
-                        "rtk_dt_ns": "",
-                        "rtk_prev_dt_ns": "",
-                        "rtk_next_dt_ns": "",
-                        "rtk_lat": "",
-                        "rtk_lon": "",
-                        "rtk_alt_m": "",
-                        "rtk_vehicle_heading_deg": "",
-                        "rtk_raw_heading_deg": "",
-                        "rtk_fix": "",
-                        "rtk_sat": "",
-                        "rtk_position_valid": "",
-                        "rtk_heading_valid": "",
-                        "rtk_heading_solution": "",
-                    }
-                )
-            try:
-                dorec_path = choose_dorec(dorec_index, record.source_dorec)
-                record_meta, payload = read_record(dorec_path, record)
-                frame_counter, point_count, raw_points = parse_lidar_payload(payload)
-                timestamp_iso, unix_ns = dotnet_ticks_to_values(record.dotnet_ticks, tz)
-                filename = frame_filename(record, frame_counter, extension)
-                relative_output = (Path("frames") / filename).as_posix()
-                frame_path = output / relative_output
-                metadata: dict[str, object] = {
-                    "format_version": FORMAT_VERSION,
-                    "sequence": record.sequence,
-                    "object_name": record.object_name,
-                    "dotnet_ticks": record.dotnet_ticks,
-                    "timestamp_iso_local": timestamp_iso,
-                    "unix_time_ns": unix_ns,
-                    "timezone": args.timezone,
-                    "log_time": record.log_time,
-                    "record_id": record_meta["record_id"],
-                    "record_id_bytes_hex": record_meta["record_id_bytes_hex"],
-                    "frame_counter": frame_counter,
-                    "point_count": point_count,
-                    "payload_length": record_meta["payload_length"],
-                    "source_log": record.source_log,
-                    "source_dorec": record.source_dorec,
-                    "source_offset": record.source_offset,
-                    "point_columns": ["d_mm", "azimuth_deg", "altitude_deg", "intensity", "progression"],
-                    "extrinsic": {
-                        "translation_mm": list(translation),
-                        "yaw_pitch_roll_deg": [args.yaw, args.pitch, args.roll],
-                        "rotation_row_major": list(rotation),
-                    },
-                }
-                rtk_arrays = None
-                match_info: dict[str, object] | None = None
-                if include_rtk:
-                    match_info = match_rtk(unix_ns, gps_post_z)
-                    sample: RtkSample | None = match_info["sample"]  # type: ignore[assignment]
-                    if match_info["matched"]:
-                        matched_frames += 1
-                        dt_ns = int(match_info["dt_ns"])
-                        match_dts_ns.append(dt_ns)
-                        prev_i = int(match_info["prev_index"])
-                        next_i = int(match_info["next_index"])
-                        if prev_i < 0 or next_i < 0:
-                            edge_frames += 1
-                        else:
-                            interior_dts_ns.append(dt_ns)
-                    else:
-                        unmatched_frames += 1
-                    rtk_meta = {
-                        "matched": bool(match_info["matched"]),
-                        "nearest_index": match_info["nearest_index"],
-                        "prev_index": match_info["prev_index"],
-                        "next_index": match_info["next_index"],
-                        "dt_ns": match_info["dt_ns"],
-                        "prev_dt_ns": match_info["prev_dt_ns"],
-                        "next_dt_ns": match_info["next_dt_ns"],
-                        "primary_source": "GPS-POST-Z",
-                    }
-                    if sample is not None:
-                        rtk_meta.update(
-                            {
-                                "dotnet_ticks": sample.dotnet_ticks,
-                                "unix_time_ns": sample.unix_time_ns,
-                                "timestamp_iso_local": sample.timestamp_iso_local,
-                                "lat": sample.lat,
-                                "lon": sample.lon,
-                                "alt_m": sample.alt_m,
-                                "raw_heading_deg": sample.raw_heading_deg,
-                                "vehicle_heading_deg": sample.vehicle_heading_deg,
-                                "fix": sample.fix,
-                                "sat": sample.sat,
-                                "position_valid": sample.position_valid,
-                                "heading_valid": sample.heading_valid,
-                                "heading_solution": sample.heading_solution,
-                                "position_time": sample.position_time,
-                                "heading_time": sample.heading_time,
-                                "last_line": sample.last_line,
-                                "counter": sample.counter,
-                                "record_id": sample.record_id,
-                                "source_dorec": sample.source_dorec,
-                                "source_offset": sample.source_offset,
-                            }
-                        )
-                    metadata["rtk"] = rtk_meta
-                    rtk_arrays = rtk_frame_arrays(match_info)
-                    row.update(
-                        {
-                            "rtk_matched": bool(match_info["matched"]),
-                            "rtk_nearest_index": match_info["nearest_index"],
-                            "rtk_prev_index": match_info["prev_index"],
-                            "rtk_next_index": match_info["next_index"],
-                            "rtk_dt_ns": "" if match_info["dt_ns"] is None else match_info["dt_ns"],
-                            "rtk_prev_dt_ns": "" if match_info["prev_dt_ns"] is None else match_info["prev_dt_ns"],
-                            "rtk_next_dt_ns": "" if match_info["next_dt_ns"] is None else match_info["next_dt_ns"],
-                            "rtk_lat": "" if sample is None or sample.lat is None else sample.lat,
-                            "rtk_lon": "" if sample is None or sample.lon is None else sample.lon,
-                            "rtk_alt_m": "" if sample is None or sample.alt_m is None else sample.alt_m,
-                            "rtk_vehicle_heading_deg": (
-                                "" if sample is None or sample.vehicle_heading_deg is None else sample.vehicle_heading_deg
-                            ),
-                            "rtk_raw_heading_deg": (
-                                "" if sample is None or sample.raw_heading_deg is None else sample.raw_heading_deg
-                            ),
-                            "rtk_fix": "" if sample is None or sample.fix is None else sample.fix,
-                            "rtk_sat": "" if sample is None or sample.sat is None else sample.sat,
-                            "rtk_position_valid": "" if sample is None else sample.position_valid,
-                            "rtk_heading_valid": "" if sample is None else sample.heading_valid,
-                            "rtk_heading_solution": "" if sample is None else sample.heading_solution,
-                        }
-                    )
-                    if match_writer is not None:
-                        match_writer.writerow(
-                            {
-                                "sequence": record.sequence,
-                                "lidar_unix_time_ns": unix_ns,
-                                "lidar_dotnet_ticks": record.dotnet_ticks,
-                                "output_file": relative_output,
-                                "rtk_matched": bool(match_info["matched"]),
-                                "rtk_nearest_index": match_info["nearest_index"],
-                                "rtk_prev_index": match_info["prev_index"],
-                                "rtk_next_index": match_info["next_index"],
-                                "rtk_dt_ns": "" if match_info["dt_ns"] is None else match_info["dt_ns"],
-                                "rtk_prev_dt_ns": "" if match_info["prev_dt_ns"] is None else match_info["prev_dt_ns"],
-                                "rtk_next_dt_ns": "" if match_info["next_dt_ns"] is None else match_info["next_dt_ns"],
-                                "rtk_dotnet_ticks": "" if sample is None else sample.dotnet_ticks,
-                                "rtk_unix_time_ns": "" if sample is None else sample.unix_time_ns,
-                                "rtk_lat": "" if sample is None else sample.lat,
-                                "rtk_lon": "" if sample is None else sample.lon,
-                                "rtk_alt_m": "" if sample is None else sample.alt_m,
-                                "rtk_raw_heading_deg": "" if sample is None else sample.raw_heading_deg,
-                                "rtk_vehicle_heading_deg": "" if sample is None else sample.vehicle_heading_deg,
-                                "rtk_fix": "" if sample is None else sample.fix,
-                                "rtk_sat": "" if sample is None else sample.sat,
-                                "rtk_position_valid": "" if sample is None else sample.position_valid,
-                                "rtk_heading_valid": "" if sample is None else sample.heading_valid,
-                                "rtk_heading_solution": "" if sample is None else sample.heading_solution,
-                                "rtk_position_time": "" if sample is None else sample.position_time,
-                                "rtk_heading_time": "" if sample is None else sample.heading_time,
-                                "rtk_last_line": "" if sample is None else sample.last_line,
-                                "rtk_source_dorec": "" if sample is None else sample.source_dorec,
-                                "rtk_source_offset": "" if sample is None else sample.source_offset,
-                            }
-                        )
-
-                row.update(
-                    {
-                        "timestamp_iso_local": timestamp_iso,
-                        "unix_time_ns": unix_ns,
-                        "record_id": record_meta["record_id"],
-                        "record_id_bytes_hex": record_meta["record_id_bytes_hex"],
-                        "frame_counter": frame_counter,
-                        "point_count": point_count,
-                        "output_file": relative_output,
-                    }
-                )
-                if args.resume and frame_path.exists():
-                    row["status"] = "resumed"
-                    resumed += 1
-                else:
-                    xyz_sensor, xyz_cart = generate_xyz(raw_points, args.include_xyz, translation, rotation)
-                    if args.format == "npz":
-                        export_npz(
-                            frame_path,
-                            metadata,
-                            raw_points,
-                            point_count,
-                            xyz_sensor,
-                            xyz_cart,
-                            args.compress,
-                            rtk_arrays=rtk_arrays,
-                        )
-                    else:
-                        export_pickle(frame_path, metadata, raw_points, point_count, xyz_sensor, xyz_cart)
-                    row["status"] = "exported"
-                    exported += 1
-                total_points += point_count
-            except Exception as exc:
-                skipped += 1
-                row["error"] = f"{type(exc).__name__}: {exc}"
-            writer.writerow(row)
-            if (selected_index + 1) % 25 == 0 or selected_index + 1 == len(selected):
-                manifest_stream.flush()
-                if match_stream is not None:
-                    match_stream.flush()
-                print(
-                    f"[{selected_index + 1}/{len(selected)}] exported={exported} resumed={resumed} "
-                    f"errors={skipped} points={total_points}",
-                    flush=True,
-                )
-
-    if match_stream is not None:
-        match_stream.close()
-        if write_reports and match_tmp is not None and match_final is not None:
-            os.replace(match_tmp, match_final)
-    if write_reports and manifest_tmp is not None and manifest_final is not None:
-        os.replace(manifest_tmp, manifest_final)
-
-    lidar_stats = {
-        "records_discovered": len(records),
-        "records_selected": len(selected),
-        "frames_exported": exported,
-        "frames_resumed": resumed,
-        "frames_with_errors": skipped,
-        "total_points_in_manifest": total_points,
-    }
-    validation = build_validation_report(
-        lidar_stats=lidar_stats,
-        gps_post_z_stats=gps_post_z_stats,
-        rtk_binary_stats=rtk_binary_stats,
-        gps_post_stats=gps_post_stats,
-        text_stats=text_stats,
-        match_dts_ns=match_dts_ns,
-        interior_dts_ns=interior_dts_ns,
-        edge_frames=edge_frames,
-        matched_frames=matched_frames,
-        unmatched_frames=unmatched_frames,
-        rtk_max_dt_ms=args.rtk_max_dt_ms,
-        rtk_sidecars=rtk_sidecars,
-    )
-
-    write_package_readme(
-        output / "README.md",
-        format_version=FORMAT_VERSION,
-        frame_count=exported + resumed,
-        include_rtk=include_rtk,
-        timezone_text=args.timezone,
-    )
-
-    metadata = {
-        "format_version": FORMAT_VERSION,
-        "generated_at": datetime.now().astimezone().isoformat(),
-        "source_dlog": str(root),
-        "object_name": args.object,
-        "output_format": args.format,
-        "npz_compressed": bool(args.compress and args.format == "npz"),
-        "include_xyz": args.include_xyz,
-        "include_rtk": include_rtk,
-        "rtk_sidecars": rtk_sidecars,
-        "write_reports": write_reports,
-        "timezone": args.timezone,
-        "timezone_offset_minutes": timezone_minutes(tz),
-        "rtk_max_dt_ms": args.rtk_max_dt_ms,
-        "rtk_objects": list(RTK_OBJECT_NAMES),
-        "rtk_outputs": rtk_outputs if rtk_sidecars else None,
-        "package_contents": ["README.md", "frames/"]
-        + (["rtk/"] if rtk_sidecars else [])
-        + (["reports/"] if write_reports else []),
-        **lidar_stats,
-        "point_columns": [
-            {"name": "d_mm", "dtype": "float32", "unit": "mm"},
-            {"name": "azimuth_deg", "dtype": "float32", "unit": "degree"},
-            {"name": "altitude_deg", "dtype": "float32", "unit": "degree"},
-            {"name": "intensity", "dtype": "float32", "unit": "device-specific"},
-            {"name": "progression", "dtype": "float32", "unit": "scan fraction"},
-        ],
-        "extrinsic": {
-            "translation_mm": list(translation),
-            "yaw_pitch_roll_deg": [args.yaw, args.pitch, args.roll],
-            "rotation_row_major": list(rotation),
-        },
-        "validation_ok": validation["ok"],
-        "duration_seconds": round(time.time() - started, 3),
-    }
-    if write_reports:
-        with (reports_dir / "metadata.json").open("w", encoding="utf-8") as stream:
-            json.dump(metadata, stream, ensure_ascii=False, indent=2)
-            stream.write("\n")
-        with (reports_dir / "validation_report.json").open("w", encoding="utf-8") as stream:
-            json.dump(validation, stream, ensure_ascii=False, indent=2)
-            stream.write("\n")
-
-    print(json.dumps(metadata, ensure_ascii=False, indent=2), flush=True)
-    print(
-        json.dumps(
-            {"validation_ok": validation["ok"], "checks": validation["checks"]},
-            ensure_ascii=False,
-            indent=2,
-        ),
-        flush=True,
-    )
-    if skipped != 0:
-        return 1
-    if include_rtk and not validation["ok"]:
-        return 1
-    return 0
-
-
-def main() -> int:
-    try:
-        return export_dataset(parse_args())
-    except Exception as exc:
-        print(f"ERROR: {type(exc).__name__}: {exc}", file=sys.stderr)
-        return 2
-
-
-if __name__ == "__main__":
-    raise SystemExit(main())
diff --git a/LiDAR_RTK_Direct_Calibration/tools/prepare_multisensor_station_dataset.py b/LiDAR_RTK_Direct_Calibration/tools/prepare_multisensor_station_dataset.py
deleted file mode 100644
index c47fdc5..0000000
--- a/LiDAR_RTK_Direct_Calibration/tools/prepare_multisensor_station_dataset.py
+++ /dev/null
@@ -1,170 +0,0 @@
-#!/usr/bin/env python3
-"""Prepare one static LiDAR frame and one yaw-only RTK reference pose per NPZ segment."""
-
-from __future__ import annotations
-
-import argparse
-import csv
-import json
-import math
-import re
-import shutil
-from pathlib import Path
-from typing import Any
-
-import numpy as np
-
-POSE_FIELDS = ["time", "x", "y", "z", "qx", "qy", "qz", "qw"]
-
-
-def natural_key(value: str) -> list[Any]:
-    return [int(part) if part.isdigit() else part.lower() for part in re.split(r"(\d+)", value)]
-
-
-def truth(value: Any) -> bool:
-    return str(value).strip().lower() in {"1", "true", "yes", "y"}
-
-
-def circular_mean_deg(values: np.ndarray) -> float:
-    radians = np.deg2rad(values)
-    return float(np.rad2deg(math.atan2(np.mean(np.sin(radians)), np.mean(np.cos(radians)))) % 360.0)
-
-
-def circular_std_deg(values: np.ndarray) -> float:
-    radians = np.deg2rad(values)
-    resultant = max(math.hypot(np.mean(np.cos(radians)), np.mean(np.sin(radians))), 1e-12)
-    return float(np.rad2deg(math.sqrt(-2.0 * math.log(resultant))))
-
-
-def geodetic_to_ecef(lat_deg: float, lon_deg: float, height_m: float) -> np.ndarray:
-    a, e2 = 6378137.0, 6.69437999014e-3
-    lat, lon = math.radians(lat_deg), math.radians(lon_deg)
-    sin_lat, cos_lat, sin_lon, cos_lon = math.sin(lat), math.cos(lat), math.sin(lon), math.cos(lon)
-    n = a / math.sqrt(1.0 - e2 * sin_lat * sin_lat)
-    return np.array([(n + height_m) * cos_lat * cos_lon, (n + height_m) * cos_lat * sin_lon,
-                     (n * (1.0 - e2) + height_m) * sin_lat], dtype=float)
-
-
-def ecef_to_enu(ecef: np.ndarray, origin: np.ndarray, lat_deg: float, lon_deg: float) -> np.ndarray:
-    lat, lon = math.radians(lat_deg), math.radians(lon_deg)
-    slat, clat, slon, clon = math.sin(lat), math.cos(lat), math.sin(lon), math.cos(lon)
-    rotation = np.array([[-slon, clon, 0.0], [-slat * clon, -slat * slon, clat],
-                         [clat * clon, clat * slon, slat]], dtype=float)
-    return rotation @ (ecef - origin)
-
-
-def yaw_rotation(yaw: float) -> np.ndarray:
-    c, s = math.cos(yaw), math.sin(yaw)
-    return np.array([[c, -s, 0.0], [s, c, 0.0], [0.0, 0.0, 1.0]])
-
-
-def scalar(data: np.lib.npyio.NpzFile, name: str) -> float:
-    return float(np.asarray(data[name]).reshape(-1)[0])
-
-
-def parse_args() -> argparse.Namespace:
-    parser = argparse.ArgumentParser(description=__doc__)
-    parser.add_argument("--combined-root", type=Path, required=True)
-    parser.add_argument("--output", type=Path, required=True)
-    parser.add_argument("--pose-name", default="rtk_gga_raw_heading")
-    parser.add_argument("--heading-offset-deg", type=float, required=True)
-    parser.add_argument("--antenna-lever", type=float, nargs=3, required=True, metavar=("X", "Y", "Z"))
-    parser.add_argument("--accepted-fixes", type=int, nargs="+", default=[4, 5])
-    parser.add_argument("--heading-std-limit-deg", type=float, default=0.5)
-    parser.add_argument("--min-stations", type=int, default=30)
-    parser.add_argument("--expected-stations", type=int, default=0)
-    parser.add_argument("--overwrite", action="store_true")
-    return parser.parse_args()
-
-
-def main() -> int:
-    args = parse_args()
-    manifest_path = args.combined_root / "manifest.csv"
-    with manifest_path.open("r", encoding="utf-8-sig", newline="") as stream:
-        rows = list(csv.DictReader(stream))
-    required = {"segment", "output", "lidar_time_ns", "rtk_valid", "heading_valid", "rtk_fix_quality"}
-    if not rows or not required.issubset(rows[0]):
-        raise ValueError(f"{manifest_path} is empty or lacks {sorted(required)}")
-    groups: dict[str, list[dict[str, str]]] = {}
-    for row in rows:
-        groups.setdefault(row["segment"], []).append(row)
-
-    selected, summaries, rejected = [], [], []
-    accepted_fixes = set(args.accepted_fixes)
-    for segment in sorted(groups, key=natural_key):
-        group = sorted(groups[segment], key=lambda row: int(row["lidar_time_ns"]))
-        good = [row for row in group if truth(row["rtk_valid"]) and truth(row["heading_valid"])
-                and int(row["rtk_fix_quality"]) in accepted_fixes]
-        if not good:
-            rejected.append({"station": segment, "reason": "no associated fixed RTK position and valid heading"})
-            continue
-        samples = []
-        for row in good:
-            path = args.combined_root / Path(row["output"])
-            with np.load(path, allow_pickle=False) as data:
-                samples.append((scalar(data, "rtk_lat_deg"), scalar(data, "rtk_lon_deg"),
-                                scalar(data, "rtk_altitude_m"), scalar(data, "rtk_raw_heading_deg"),
-                                scalar(data, "rtk_pitch_deg"), scalar(data, "rtk_heading_stddev_deg")))
-        values = np.asarray(samples, dtype=float)
-        heading_std = circular_std_deg(values[:, 3])
-        if heading_std > args.heading_std_limit_deg:
-            rejected.append({"station": segment, "reason": f"heading std {heading_std:.4f} deg exceeds limit"})
-            continue
-        frame = good[len(good) // 2]
-        source = args.combined_root / Path(frame["output"])
-        selected.append({"station": segment, "source": source, "time": int(frame["lidar_time_ns"]) / 1e9,
-                         "lat": float(np.mean(values[:, 0])), "lon": float(np.mean(values[:, 1])),
-                         "alt": float(np.mean(values[:, 2])), "heading": circular_mean_deg(values[:, 3])})
-        summaries.append({"station": segment, "frames": len(group), "valid_fixed_frames": len(good),
-                          "heading_mean_deg": circular_mean_deg(values[:, 3]),
-                          "heading_circular_std_deg": heading_std, "rtk_pitch_mean_deg": float(np.mean(values[:, 4])),
-                          "reported_heading_std_mean_deg": float(np.nanmean(values[:, 5])),
-                          "altitude_std_m": float(np.std(values[:, 2])), "selected_source": str(source)})
-
-    if args.expected_stations and len(selected) != args.expected_stations:
-        raise RuntimeError(f"expected {args.expected_stations} usable stations, got {len(selected)}; rejected={rejected}")
-    if len(selected) < args.min_stations:
-        raise RuntimeError(f"need at least {args.min_stations} usable stations, got {len(selected)}; rejected={rejected}")
-    if args.output.exists() and any(args.output.iterdir()) and not args.overwrite:
-        raise FileExistsError(f"{args.output} is non-empty; pass --overwrite")
-    frames = args.output / "frames_all"
-    frames.mkdir(parents=True, exist_ok=True)
-    origin = selected[0]
-    origin_ecef = geodetic_to_ecef(origin["lat"], origin["lon"], origin["alt"])
-    lever = np.asarray(args.antenna_lever, dtype=float)
-    pose_rows = []
-    for index, item in enumerate(selected, 1):
-        destination = frames / f"station_{index:02d}.npz"
-        shutil.copy2(item["source"], destination)
-        antenna = ecef_to_enu(geodetic_to_ecef(item["lat"], item["lon"], item["alt"]), origin_ecef,
-                              origin["lat"], origin["lon"])
-        corrected_heading = (item["heading"] + args.heading_offset_deg) % 360.0
-        yaw = math.radians(90.0 - corrected_heading)
-        reference_position = antenna - yaw_rotation(yaw) @ lever
-        pose_rows.append(dict(zip(POSE_FIELDS, [item["time"], *reference_position, 0.0, 0.0,
-                                                math.sin(yaw / 2.0), math.cos(yaw / 2.0)])))
-        summaries[index - 1].update({"sequence": index, "prepared_frame": destination.name,
-                                     "corrected_heading_deg": corrected_heading})
-    pose_path = args.output / f"reference_poses_{args.pose_name}.csv"
-    with pose_path.open("w", encoding="utf-8", newline="") as stream:
-        writer = csv.DictWriter(stream, fieldnames=POSE_FIELDS); writer.writeheader(); writer.writerows(pose_rows)
-    with (args.output / "station_summary.csv").open("w", encoding="utf-8", newline="") as stream:
-        fields = sorted({key for row in summaries for key in row})
-        writer = csv.DictWriter(stream, fieldnames=fields); writer.writeheader(); writer.writerows(summaries)
-    document = {"source_combined_root": str(args.combined_root.resolve()), "station_count": len(selected),
-                "rejected": rejected, "pose_csv": pose_path.name,
-                "selection_policy": "middle LiDAR frame among fixed-position and valid-heading associations",
-                "reference_pose_configuration": {"raw_heading_offset_deg": args.heading_offset_deg,
-                    "antenna_lever_body_m": args.antenna_lever,
-                    "orientation_model": "yaw-only, identical to the previous calibration workflow"},
-                "stations": [{"sequence": i + 1, "source_station": item["station"],
-                              "source_frame": str(item["source"]), "prepared_frame": f"station_{i + 1:02d}.npz"}
-                             for i, item in enumerate(selected)]}
-    (args.output / "manifest.json").write_text(json.dumps(document, ensure_ascii=False, indent=2), encoding="utf-8")
-    print(json.dumps({"prepared": str(args.output.resolve()), "stations": len(selected),
-                      "rejected": rejected, "pose_csv": pose_path.name}, ensure_ascii=False, indent=2))
-    return 0
-
-
-if __name__ == "__main__":
-    raise SystemExit(main())
diff --git a/LiDAR_RTK_Direct_Calibration/tools/rscap_v2/audit_capture_v2.py b/LiDAR_RTK_Direct_Calibration/tools/rscap_v2/audit_capture_v2.py
deleted file mode 100644
index 4d8bb77..0000000
--- a/LiDAR_RTK_Direct_Calibration/tools/rscap_v2/audit_capture_v2.py
+++ /dev/null
@@ -1,22 +0,0 @@
-from __future__ import annotations
-
-import argparse
-from pathlib import Path
-
-from capture_format_v2 import file_summary, read_capture
-from pipeline_common import write_json
-
-
-def main() -> None:
-    parser = argparse.ArgumentParser()
-    parser.add_argument("captures", nargs="+", type=Path)
-    parser.add_argument("--out", type=Path, required=True)
-    args = parser.parse_args()
-    summaries = [file_summary(read_capture(path)) for path in args.captures]
-    write_json(args.out, {"captures": summaries})
-    for summary in summaries:
-        print(summary)
-
-
-if __name__ == "__main__":
-    main()
diff --git a/LiDAR_RTK_Direct_Calibration/tools/rscap_v2/capture_format_v2.py b/LiDAR_RTK_Direct_Calibration/tools/rscap_v2/capture_format_v2.py
deleted file mode 100644
index 3812980..0000000
--- a/LiDAR_RTK_Direct_Calibration/tools/rscap_v2/capture_format_v2.py
+++ /dev/null
@@ -1,254 +0,0 @@
-from __future__ import annotations
-
-import binascii
-import io
-import struct
-from dataclasses import dataclass, asdict
-from pathlib import Path
-from typing import BinaryIO, Iterator
-
-
-FILE_MAGIC = "RAW_SERIAL_CAPTURE_FILE_V2"
-RECORD_MAGIC = "RAW_SERIAL_RECORD_V2"
-FOOTER_MAGIC = "RAW_SERIAL_CAPTURE_FOOTER_V2"
-
-
-def read_7bit_int(stream: BinaryIO) -> int:
-    value = 0
-    shift = 0
-    while True:
-        raw = stream.read(1)
-        if not raw:
-            raise EOFError("truncated .NET string length")
-        value |= (raw[0] & 0x7F) << shift
-        if not raw[0] & 0x80:
-            return value
-        shift += 7
-        if shift > 35:
-            raise ValueError("invalid .NET string length")
-
-
-def read_dotnet_string(stream: BinaryIO) -> str:
-    length = read_7bit_int(stream)
-    raw = stream.read(length)
-    if len(raw) != length:
-        raise EOFError("truncated .NET string")
-    return raw.decode("utf-8")
-
-
-def read_i32(stream: BinaryIO) -> int:
-    raw = stream.read(4)
-    if len(raw) != 4:
-        raise EOFError("truncated int32")
-    return struct.unpack("<i", raw)[0]
-
-
-def read_i64(stream: BinaryIO) -> int:
-    raw = stream.read(8)
-    if len(raw) != 8:
-        raise EOFError("truncated int64")
-    return struct.unpack("<q", raw)[0]
-
-
-def read_u32(stream: BinaryIO) -> int:
-    raw = stream.read(4)
-    if len(raw) != 4:
-        raise EOFError("truncated uint32")
-    return struct.unpack("<I", raw)[0]
-
-
-@dataclass(frozen=True)
-class CaptureHeader:
-    sensor_kind: str
-    session_id: str
-    session_start_utc_ticks: int
-    session_start_monotonic_ticks: int
-    monotonic_frequency: int
-    port: str
-    baud: int
-    file_start_utc_ticks: int
-
-
-@dataclass(frozen=True)
-class RawChunk:
-    sequence: int
-    receive_utc_ticks: int
-    receive_monotonic_ticks: int
-    raw: bytes
-    record_file_offset: int
-    raw_file_offset: int
-    record_crc32: int
-    crc_valid: bool
-
-
-@dataclass(frozen=True)
-class CaptureFooter:
-    clean_close: bool
-    records: int
-    bytes: int
-    first_sequence: int
-    last_sequence: int
-    dropped_chunks: int
-    dropped_bytes: int
-    crc_valid: bool
-
-
-@dataclass
-class CaptureFile:
-    path: str
-    header: CaptureHeader
-    chunks: list[RawChunk]
-    footer: CaptureFooter | None
-    truncated_tail: bool = False
-
-
-def read_header(stream: BinaryIO) -> CaptureHeader:
-    if read_dotnet_string(stream) != FILE_MAGIC:
-        raise ValueError("not a V2 raw capture file")
-    version = read_i32(stream)
-    if version != 2:
-        raise ValueError(f"unsupported capture version: {version}")
-    return CaptureHeader(
-        sensor_kind=read_dotnet_string(stream),
-        session_id=read_dotnet_string(stream),
-        session_start_utc_ticks=read_i64(stream),
-        session_start_monotonic_ticks=read_i64(stream),
-        monotonic_frequency=read_i64(stream),
-        port=read_dotnet_string(stream),
-        baud=read_i32(stream),
-        file_start_utc_ticks=read_i64(stream),
-    )
-
-
-def parse_record_body(body: bytes, record_file_offset: int, record_crc: int) -> RawChunk:
-    stream = io.BytesIO(body)
-    if read_dotnet_string(stream) != RECORD_MAGIC:
-        raise ValueError("invalid record magic")
-    sequence = read_i64(stream)
-    receive_utc_ticks = read_i64(stream)
-    receive_monotonic_ticks = read_i64(stream)
-    raw_length = read_i32(stream)
-    if raw_length < 0 or raw_length > 64 * 1024 * 1024:
-        raise ValueError(f"invalid raw length: {raw_length}")
-    raw_offset = record_file_offset + 4 + stream.tell()
-    raw = stream.read(raw_length)
-    if len(raw) != raw_length:
-        raise EOFError("truncated raw bytes")
-    crc_valid = (binascii.crc32(body) & 0xFFFFFFFF) == record_crc
-    return RawChunk(
-        sequence=sequence,
-        receive_utc_ticks=receive_utc_ticks,
-        receive_monotonic_ticks=receive_monotonic_ticks,
-        raw=raw,
-        record_file_offset=record_file_offset,
-        raw_file_offset=raw_offset,
-        record_crc32=record_crc,
-        crc_valid=crc_valid,
-    )
-
-
-def parse_footer(body: bytes, expected_crc: int) -> CaptureFooter:
-    stream = io.BytesIO(body)
-    if read_dotnet_string(stream) != FOOTER_MAGIC:
-        raise ValueError("invalid footer magic")
-    clean_close = stream.read(1) == b"\x01"
-    records = read_i64(stream)
-    raw_bytes = read_i64(stream)
-    first_sequence = read_i64(stream)
-    last_sequence = read_i64(stream)
-    dropped_chunks = read_i64(stream)
-    dropped_bytes = read_i64(stream)
-    return CaptureFooter(
-        clean_close=clean_close,
-        records=records,
-        bytes=raw_bytes,
-        first_sequence=first_sequence,
-        last_sequence=last_sequence,
-        dropped_chunks=dropped_chunks,
-        dropped_bytes=dropped_bytes,
-        crc_valid=(binascii.crc32(body) & 0xFFFFFFFF) == expected_crc,
-    )
-
-
-def read_capture(path: Path) -> CaptureFile:
-    chunks: list[RawChunk] = []
-    footer = None
-    truncated = False
-    with path.open("rb") as stream:
-        header = read_header(stream)
-        while True:
-            record_offset = stream.tell()
-            length_raw = stream.read(4)
-            if not length_raw:
-                break
-            if len(length_raw) != 4:
-                truncated = True
-                break
-            length = struct.unpack("<i", length_raw)[0]
-            try:
-                if length == -1:
-                    footer_length = read_i32(stream)
-                    if footer_length < 0 or footer_length > 1024 * 1024:
-                        raise ValueError("invalid footer length")
-                    footer_body = stream.read(footer_length)
-                    if len(footer_body) != footer_length:
-                        raise EOFError("truncated footer")
-                    footer = parse_footer(footer_body, read_u32(stream))
-                    break
-                if length <= 0 or length > 64 * 1024 * 1024:
-                    raise ValueError("invalid record length")
-                body = stream.read(length)
-                if len(body) != length:
-                    raise EOFError("truncated record body")
-                record_crc = read_u32(stream)
-                chunks.append(parse_record_body(body, record_offset, record_crc))
-            except (EOFError, ValueError):
-                truncated = True
-                break
-    return CaptureFile(str(path), header, chunks, footer, truncated)
-
-
-def sequence_gaps(chunks: list[RawChunk]) -> list[tuple[int, int, int]]:
-    result = []
-    for previous, current in zip(chunks, chunks[1:]):
-        if current.sequence > previous.sequence + 1:
-            result.append((previous.sequence, current.sequence, current.sequence - previous.sequence - 1))
-    return result
-
-
-def file_summary(capture: CaptureFile) -> dict:
-    gaps = sequence_gaps(capture.chunks)
-    sequences = [chunk.sequence for chunk in capture.chunks]
-    return {
-        "path": capture.path,
-        "sensor": capture.header.sensor_kind,
-        "session_id": capture.header.session_id,
-        "port": capture.header.port,
-        "baud": capture.header.baud,
-        "chunks_read": len(capture.chunks),
-        "bytes_read": sum(len(chunk.raw) for chunk in capture.chunks),
-        "first_sequence": sequences[0] if sequences else None,
-        "last_sequence": sequences[-1] if sequences else None,
-        "missing_chunks": sum(gap[2] for gap in gaps),
-        "gap_count": len(gaps),
-        "bad_record_crc": sum(not chunk.crc_valid for chunk in capture.chunks),
-        "truncated_tail": capture.truncated_tail,
-        "footer": None if capture.footer is None else asdict(capture.footer),
-        "gaps": gaps[:100],
-    }
-
-
-def iter_contiguous_segments(chunks: list[RawChunk]) -> Iterator[tuple[int, list[RawChunk]]]:
-    if not chunks:
-        return
-    segment_id = 0
-    current = [chunks[0]]
-    for previous, chunk in zip(chunks, chunks[1:]):
-        if chunk.sequence != previous.sequence + 1:
-            yield segment_id, current
-            segment_id += 1
-            current = [chunk]
-        else:
-            current.append(chunk)
-    yield segment_id, current
-
diff --git a/LiDAR_RTK_Direct_Calibration/tools/rscap_v2/parse_rtk_imu_v2.py b/LiDAR_RTK_Direct_Calibration/tools/rscap_v2/parse_rtk_imu_v2.py
deleted file mode 100644
index d30a115..0000000
--- a/LiDAR_RTK_Direct_Calibration/tools/rscap_v2/parse_rtk_imu_v2.py
+++ /dev/null
@@ -1,35 +0,0 @@
-from __future__ import annotations
-
-import argparse
-from pathlib import Path
-
-from capture_format_v2 import file_summary, read_capture
-from pipeline_common_corrected import parse_imu_capture, parse_rtk_capture, write_json, write_jsonl
-
-
-def main() -> None:
-    parser = argparse.ArgumentParser()
-    parser.add_argument("--rtk", type=Path, required=True)
-    parser.add_argument("--imu", type=Path, required=True)
-    parser.add_argument("--out", type=Path, required=True)
-    args = parser.parse_args()
-    args.out.mkdir(parents=True, exist_ok=True)
-    rtk_capture = read_capture(args.rtk)
-    imu_capture = read_capture(args.imu)
-    rtk_rows = parse_rtk_capture(rtk_capture)
-    imu_rows = parse_imu_capture(imu_capture)
-    write_jsonl(args.out / "rtk.jsonl", rtk_rows)
-    write_jsonl(args.out / "imu.jsonl", imu_rows)
-    write_json(args.out / "parse_summary.json", {
-        "rtk_capture": file_summary(rtk_capture),
-        "imu_capture": file_summary(imu_capture),
-        "rtk_records": len(rtk_rows),
-        "rtk_checksum_valid": sum(bool(row.get("checksum_valid")) for row in rtk_rows),
-        "imu_frames": len(imu_rows),
-        "imu_crc_valid": sum(bool(row.get("crc_valid")) for row in imu_rows),
-    })
-    print(f"RTK records={len(rtk_rows)}, IMU frames={len(imu_rows)}")
-
-
-if __name__ == "__main__":
-    main()
diff --git a/LiDAR_RTK_Direct_Calibration/tools/rscap_v2/pipeline_common.py b/LiDAR_RTK_Direct_Calibration/tools/rscap_v2/pipeline_common.py
deleted file mode 100644
index 3f733ce..0000000
--- a/LiDAR_RTK_Direct_Calibration/tools/rscap_v2/pipeline_common.py
+++ /dev/null
@@ -1,300 +0,0 @@
-from __future__ import annotations
-
-import binascii
-import json
-import math
-import struct
-from pathlib import Path
-from typing import Iterable
-
-from capture_format_v2 import CaptureFile, RawChunk, iter_contiguous_segments, read_capture
-
-
-DOTNET_UNIX_EPOCH_TICKS = 621355968000000000
-
-
-def ticks_to_unix_ns(ticks: int) -> int:
-    return (ticks - DOTNET_UNIX_EPOCH_TICKS) * 100
-
-
-def safe_float(value: str, default=None):
-    try:
-        return float(value)
-    except (TypeError, ValueError):
-        return default
-
-
-def safe_int(value: str, default=None):
-    try:
-        return int(value)
-    except (TypeError, ValueError):
-        return default
-
-
-def nmea_checksum_valid(line: str) -> bool:
-    star = line.rfind("*")
-    if star < 0:
-        return False
-    try:
-        expected = int(line[star + 1:star + 3], 16)
-    except ValueError:
-        return False
-    value = 0
-    for char in line[1:star]:
-        value ^= ord(char)
-    return value == expected
-
-
-def unicore_crc32(text: str) -> int:
-    crc = 0
-    for value in text.encode("ascii", "replace"):
-        crc ^= value
-        for _ in range(8):
-            crc = (crc >> 1) ^ (0xEDB88320 if crc & 1 else 0)
-    return crc & 0xFFFFFFFF
-
-
-def unicore_checksum_valid(line: str) -> bool:
-    star = line.rfind("*")
-    if star < 0 or len(line) < star + 9:
-        return False
-    try:
-        expected = int(line[star + 1:star + 9], 16)
-    except ValueError:
-        return False
-    return unicore_crc32(line[1:star]) == expected
-
-
-def parse_checksum(line: str) -> bool:
-    if line.startswith("$"):
-        return nmea_checksum_valid(line)
-    if line.startswith("#"):
-        return unicore_checksum_valid(line)
-    return False
-
-
-def parse_nmea_latlon(value: str, hemisphere: str):
-    raw = safe_float(value)
-    if raw is None:
-        return None
-    degrees = math.floor(raw / 100.0)
-    result = degrees + (raw - degrees * 100.0) / 60.0
-    if hemisphere.upper() in ("S", "W"):
-        result = -result
-    return result
-
-
-def parse_gga(line: str) -> dict:
-    fields = line[:line.rfind("*")].split(",")
-    if len(fields) < 10:
-        raise ValueError("GGA has too few fields")
-    return {
-        "type": "GGA",
-        "position_time_utc": fields[1],
-        "lat_deg": parse_nmea_latlon(fields[2], fields[3]),
-        "lon_deg": parse_nmea_latlon(fields[4], fields[5]),
-        "fix_quality": safe_int(fields[6], -1),
-        "satellites": safe_int(fields[7], -1),
-        "hdop": safe_float(fields[8]),
-        "altitude_m": safe_float(fields[9]),
-        "geoid_separation_m": safe_float(fields[11]) if len(fields) > 11 else None,
-        "differential_age_s": safe_float(fields[13]) if len(fields) > 13 else None,
-        "station_id": fields[14].strip('"') if len(fields) > 14 else "",
-    }
-
-
-def parse_heading(line: str) -> dict:
-    before_crc = line[:line.rfind("*")]
-    header, payload = before_crc.split(";", 1)
-    header_fields = header.split(",")
-    fields = payload.split(",")
-    if len(fields) < 7:
-        raise ValueError("UNIHEADINGA has too few fields")
-    raw_heading = safe_float(fields[3])
-    return {
-        "type": "UNIHEADINGA",
-        "gnss_week": safe_int(header_fields[4]) if len(header_fields) > 4 else None,
-        "gnss_tow_ms": safe_int(header_fields[5]) if len(header_fields) > 5 else None,
-        "heading_status": fields[0],
-        "heading_solution": fields[1],
-        "baseline_length_m": safe_float(fields[2]),
-        "raw_heading_deg": raw_heading,
-        "pitch_deg": safe_float(fields[4]),
-        "heading_stddev_deg": safe_float(fields[6]),
-        "pitch_stddev_deg": safe_float(fields[7]) if len(fields) > 7 else None,
-        "station_id": fields[8].strip('"') if len(fields) > 8 else "",
-        "satellites": safe_int(fields[9], -1) if len(fields) > 9 else -1,
-        "solution_satellites": safe_int(fields[10], -1) if len(fields) > 10 else -1,
-        "observations": safe_int(fields[11], -1) if len(fields) > 11 else -1,
-        "multi_count": safe_int(fields[12], -1) if len(fields) > 12 else -1,
-        "heading_valid": fields[0] == "SOL_COMPUTED" and fields[1] in {"NARROW_INT", "NARROW_FLOAT"},
-    }
-
-
-def chunk_source(chunks: list[RawChunk], offset: int, end: int) -> dict:
-    first = chunks[0]
-    last = chunks[-1]
-    cursor = 0
-    start_chunk = first
-    end_chunk = last
-    for chunk in chunks:
-        chunk_start = cursor
-        chunk_end = cursor + len(chunk.raw)
-        if chunk_start <= offset < chunk_end:
-            start_chunk = chunk
-        if chunk_start < end <= chunk_end:
-            end_chunk = chunk
-            break
-        cursor = chunk_end
-    return {
-        "source_segment_id": None,
-        "source_chunk_sequence_first": start_chunk.sequence,
-        "source_chunk_sequence_last": end_chunk.sequence,
-        "source_raw_file_offset": start_chunk.raw_file_offset + max(0, offset - sum(len(c.raw) for c in chunks if c.sequence < start_chunk.sequence)),
-        "source_raw_byte_length": max(0, end - offset),
-    }
-
-
-def parse_rtk_capture(capture: CaptureFile) -> list[dict]:
-    rows = []
-    for segment_id, chunks in iter_contiguous_segments(capture.chunks):
-        stream = b"".join(chunk.raw for chunk in chunks)
-        cursor = 0
-        while cursor < len(stream):
-            newline = stream.find(b"\n", cursor)
-            if newline < 0:
-                break
-            end = newline + 1
-            raw_line = stream[cursor:end].rstrip(b"\r\n")
-            cursor = end
-            if not raw_line:
-                continue
-            line = raw_line.decode("ascii", "replace")
-            valid = parse_checksum(line)
-            row = {
-                "type": "UNKNOWN",
-                "raw_line": line,
-                "checksum_valid": valid,
-                "host_receive_utc_ns": ticks_to_unix_ns(chunks[-1].receive_utc_ticks),
-                "host_receive_monotonic_ticks": chunks[-1].receive_monotonic_ticks,
-                "source_segment_id": segment_id,
-                "source_byte_offset_in_segment": cursor - len(raw_line) - 1,
-                "source_byte_length": len(raw_line) + 1,
-            }
-            try:
-                if line.startswith("$GNGGA") or line.startswith("$GPGGA"):
-                    row.update(parse_gga(line))
-                elif line.startswith("#UNIHEADINGA"):
-                    row.update(parse_heading(line))
-            except ValueError as ex:
-                row["parse_error"] = str(ex)
-            rows.append(row)
-    return rows
-
-
-def crc16_hi13(data: bytes) -> int:
-    crc = 0
-    for value in data:
-        crc ^= value << 8
-        for _ in range(8):
-            crc = ((crc << 1) ^ 0x1021) & 0xFFFF if crc & 0x8000 else (crc << 1) & 0xFFFF
-    return crc
-
-
-def decode_hi91(frame: bytes) -> dict:
-    f32 = lambda i: struct.unpack_from("<f", frame, i)[0]
-    return {
-        "tag": 0x91,
-        "pps_sync_stamp_ms": int.from_bytes(frame[7:9], "little"),
-        "temperature_c": struct.unpack_from("<b", frame, 9)[0],
-        "air_pressure_pa": f32(10),
-        "device_timestamp_ms": int.from_bytes(frame[14:18], "little"),
-        "accel_x_mps2": f32(18) * 9.80665,
-        "accel_y_mps2": f32(22) * 9.80665,
-        "accel_z_mps2": f32(26) * 9.80665,
-        "gyro_x_radps": f32(30) * math.pi / 180.0,
-        "gyro_y_radps": f32(34) * math.pi / 180.0,
-        "gyro_z_radps": f32(38) * math.pi / 180.0,
-        "mag_x_ut": f32(42), "mag_y_ut": f32(46), "mag_z_ut": f32(50),
-        "roll_deg": f32(54), "pitch_deg": f32(58), "yaw_deg": f32(62),
-        "quaternion_w": f32(66), "quaternion_x": f32(70),
-        "quaternion_y": f32(74), "quaternion_z": f32(78),
-    }
-
-
-def decode_hi92(frame: bytes) -> dict:
-    i16 = lambda i: struct.unpack_from("<h", frame, i)[0]
-    i32 = lambda i: struct.unpack_from("<i", frame, i)[0]
-    return {
-        "tag": 0x92,
-        "status": int.from_bytes(frame[7:9], "little"),
-        "temperature_c": struct.unpack_from("<b", frame, 9)[0],
-        "pps_sync_stamp_ms": int.from_bytes(frame[10:12], "little"),
-        "air_pressure_pa": i16(12) + 100000.0,
-        "heave_m": i16(14) * 0.001,
-        "gyro_x_radps": i16(16) * 0.001, "gyro_y_radps": i16(18) * 0.001, "gyro_z_radps": i16(20) * 0.001,
-        "accel_x_mps2": i16(22) * 0.0048828, "accel_y_mps2": i16(24) * 0.0048828, "accel_z_mps2": i16(26) * 0.0048828,
-        "mag_x_ut": i16(28) * 0.030517, "mag_y_ut": i16(30) * 0.030517, "mag_z_ut": i16(32) * 0.030517,
-        "roll_deg": i32(34) * 0.001, "pitch_deg": i32(38) * 0.001, "yaw_deg": i32(42) * 0.001,
-        "quaternion_w": i16(46) * 0.0001, "quaternion_x": i16(48) * 0.0001,
-        "quaternion_y": i16(50) * 0.0001, "quaternion_z": i16(52) * 0.0001,
-    }
-
-
-def parse_imu_capture(capture: CaptureFile) -> list[dict]:
-    rows = []
-    for segment_id, chunks in iter_contiguous_segments(capture.chunks):
-        stream = b"".join(chunk.raw for chunk in chunks)
-        cursor = 0
-        while True:
-            start = stream.find(b"\x5a\xa5", cursor)
-            if start < 0 or start + 6 > len(stream):
-                break
-            payload_length = int.from_bytes(stream[start + 2:start + 4], "little")
-            frame_length = 6 + payload_length
-            if payload_length <= 0 or payload_length > 512:
-                cursor = start + 1
-                continue
-            if start + frame_length > len(stream):
-                break
-            frame = stream[start:start + frame_length]
-            expected = int.from_bytes(frame[4:6], "little")
-            actual = crc16_hi13(frame[:4] + frame[6:])
-            end = start + frame_length
-            source = chunk_source(chunks, start, end)
-            source["source_segment_id"] = segment_id
-            row = {
-                "type": "HI13",
-                "tag": frame[6],
-                "frame_length": frame_length,
-                "crc_valid": expected == actual,
-                "host_receive_utc_ns": ticks_to_unix_ns(chunks[-1].receive_utc_ticks),
-                "host_receive_monotonic_ticks": chunks[-1].receive_monotonic_ticks,
-                "source_segment_id": segment_id,
-                "source_byte_offset_in_segment": start,
-                "source_byte_length": frame_length,
-                "raw_frame_hex": frame.hex(),
-            }
-            if expected == actual:
-                try:
-                    row.update(decode_hi91(frame) if frame[6] == 0x91 else decode_hi92(frame) if frame[6] == 0x92 else {})
-                except (IndexError, struct.error, ValueError) as ex:
-                    row["parse_error"] = str(ex)
-            rows.append(row)
-            cursor = end
-    return rows
-
-
-def write_jsonl(path: Path, rows: Iterable[dict]) -> None:
-    with path.open("w", encoding="utf-8", newline="\n") as stream:
-        for row in rows:
-            stream.write(json.dumps(row, ensure_ascii=False, separators=(",", ":")) + "\n")
-
-
-def write_json(path: Path, value: dict) -> None:
-    path.write_text(json.dumps(value, ensure_ascii=False, indent=2), encoding="utf-8")
-
-
-def load_jsonl(path: Path) -> list[dict]:
-    with path.open("r", encoding="utf-8") as stream:
-        return [json.loads(line) for line in stream if line.strip()]
diff --git a/LiDAR_RTK_Direct_Calibration/tools/rscap_v2/pipeline_common_corrected.py b/LiDAR_RTK_Direct_Calibration/tools/rscap_v2/pipeline_common_corrected.py
deleted file mode 100644
index 35b37ef..0000000
--- a/LiDAR_RTK_Direct_Calibration/tools/rscap_v2/pipeline_common_corrected.py
+++ /dev/null
@@ -1,106 +0,0 @@
-from __future__ import annotations
-
-import bisect
-
-from pipeline_common import *
-from capture_format_v2 import CaptureFile, RawChunk, iter_contiguous_segments
-
-
-_SPAN_CACHE: dict[int, tuple[list[RawChunk], list[int]]] = {}
-
-
-def _chunk_starts(chunks: list[RawChunk]) -> list[int]:
-    key = id(chunks)
-    cached = _SPAN_CACHE.get(key)
-    if cached is not None and cached[0] is chunks:
-        return cached[1]
-    starts = []
-    cursor = 0
-    for chunk in chunks:
-        starts.append(cursor)
-        cursor += len(chunk.raw)
-    _SPAN_CACHE[key] = (chunks, starts)
-    return starts
-
-
-def source_for_span(chunks: list[RawChunk], start: int, end: int, segment_id: int) -> dict:
-    starts = _chunk_starts(chunks)
-    start_index = max(0, min(len(chunks) - 1, bisect.bisect_right(starts, start) - 1))
-    end_index = max(start_index, min(len(chunks) - 1, bisect.bisect_left(starts, end) - 1))
-    start_chunk = chunks[start_index]
-    end_chunk = chunks[end_index]
-    return {
-        "source_segment_id": segment_id,
-        "source_chunk_sequence_first": start_chunk.sequence,
-        "source_chunk_sequence_last": end_chunk.sequence,
-        "source_raw_file_offset": start_chunk.raw_file_offset + (start - starts[start_index]),
-        "source_raw_byte_length": end - start,
-        "host_receive_utc_ns": ticks_to_unix_ns(end_chunk.receive_utc_ticks),
-        "host_receive_monotonic_ticks": end_chunk.receive_monotonic_ticks,
-    }
-
-def parse_rtk_capture(capture: CaptureFile) -> list[dict]:
-    rows = []
-    for segment_id, chunks in iter_contiguous_segments(capture.chunks):
-        stream = b"".join(chunk.raw for chunk in chunks)
-        cursor = 0
-        while cursor < len(stream):
-            newline = stream.find(b"\n", cursor)
-            if newline < 0:
-                break
-            end = newline + 1
-            raw_line = stream[cursor:end].rstrip(b"\r\n")
-            start = cursor
-            cursor = end
-            if not raw_line:
-                continue
-            line = raw_line.decode("ascii", "replace")
-            row = {"type": "UNKNOWN", "raw_line": line, "checksum_valid": parse_checksum(line)}
-            row.update(source_for_span(chunks, start, end, segment_id))
-            try:
-                if line.startswith("$GNGGA") or line.startswith("$GPGGA"):
-                    row.update(parse_gga(line))
-                elif line.startswith("#UNIHEADINGA"):
-                    row.update(parse_heading(line))
-            except ValueError as ex:
-                row["parse_error"] = str(ex)
-            rows.append(row)
-    return rows
-
-
-def parse_imu_capture(capture: CaptureFile) -> list[dict]:
-    rows = []
-    for segment_id, chunks in iter_contiguous_segments(capture.chunks):
-        stream = b"".join(chunk.raw for chunk in chunks)
-        cursor = 0
-        while True:
-            start = stream.find(b"\x5a\xa5", cursor)
-            if start < 0 or start + 6 > len(stream):
-                break
-            payload_length = int.from_bytes(stream[start + 2:start + 4], "little")
-            frame_length = 6 + payload_length
-            if payload_length <= 0 or payload_length > 512:
-                cursor = start + 1
-                continue
-            if start + frame_length > len(stream):
-                break
-            frame = stream[start:start + frame_length]
-            expected = int.from_bytes(frame[4:6], "little")
-            actual = crc16_hi13(frame[:4] + frame[6:])
-            end = start + frame_length
-            row = {
-                "type": "HI13",
-                "tag": frame[6],
-                "frame_length": frame_length,
-                "crc_valid": expected == actual,
-                "raw_frame_hex": frame.hex(),
-            }
-            row.update(source_for_span(chunks, start, end, segment_id))
-            if row["crc_valid"]:
-                try:
-                    row.update(decode_hi91(frame) if frame[6] == 0x91 else decode_hi92(frame) if frame[6] == 0x92 else {})
-                except (IndexError, struct.error, ValueError) as ex:
-                    row["parse_error"] = str(ex)
-            rows.append(row)
-            cursor = end
-    return rows
diff --git a/PAIR_DIAGNOSTICS.md b/PAIR_DIAGNOSTICS.md
deleted file mode 100644
index 72b96ae..0000000
--- a/PAIR_DIAGNOSTICS.md
+++ /dev/null
@@ -1,85 +0,0 @@
-# Pair 局部诊断与全局灵敏度扫描
-
-本说明补充主 README。所有变换均采用：
-
-```text
-X = T_body_lidar
-A_ij X = X B_ij
-B_ij = T_Li_Lj（把站点 j 点云变到站点 i）
-```
-
-模式 4 相对模式 3 的数值差定义为：
-
-```text
-Delta_ij = B_ij^-1 * (X^-1 * A_ij * X)
-```
-
-打印的平移 xyz 和旋转 RPY 是 `Delta_ij` 在站点 j 雷达局部坐标系中的分量，不是屏幕坐标。3D 相机视角会改变画面中的“横向”，所以不能仅凭屏幕左右判断车体系 Y 或 yaw。
-
-## Pair 0 当前诊断
-
-Open3D 精筛 Pair 0（station 0 <- 1）的当前结果为：
-
-```text
-translation xyz = [-1.2535, +1.4157, +7.7441] cm
-rotation RPY xyz = [-0.5355, -0.1093, +0.0247] deg
-norm = 7.9716 cm / 0.547109 deg
-```
-
-因此这对主要表现为 roll/pitch 相关姿态差和相对 Z 差，yaw 仅约 `0.025 deg`，不应优先调 yaw。
-
-## 可视化试验
-
-查看原结果：
-
-```powershell
-$Repo = "D:\你的代码目录\calibration"
-powershell.exe -NoProfile -ExecutionPolicy Bypass -File "$Repo\run\view_open3d_result.ps1" -PairIndex 0
-```
-
-试验车体系左乘 pitch `+0.2 deg`：
-
-```powershell
-powershell.exe -NoProfile -ExecutionPolicy Bypass -File "$Repo\run\view_open3d_result.ps1" -PairIndex 0 -LeftPitchDeg 0.2
-```
-
-此时按键含义：`3` 为 GICP 的 B，`4` 为当前最终 X 预测，`5` 为试验修正后的 X 预测。试验使用：
-
-```text
-X_test = DeltaR_body * X
-```
-
-这是真正的车体系左乘，会同时旋转 X 的旋转部分和平移向量；小角度下才近似等价于直接给 JSON 的 pitch 加相同角度。
-
-## 全部运动对扫描
-
-运行：
-
-```powershell
-powershell.exe -NoProfile -ExecutionPolicy Bypass -File "$Repo\run\run_sensitivity_scan.ps1" -PairIndex 0
-```
-
-程序扫描：
-
-- pitch：`+0.1/+0.2/+0.3 deg`；
-- 在这些 pitch 及零 pitch 附近扫描 roll：`-0.2/-0.1/+0.1 deg`；
-- yaw `-0.2/+0.2 deg` 只作为低灵敏度对照；
-- Open3D 全部精筛对、small_gicp 全部精筛对、跨后端共识对分别计算；
-- 同时报告地面法向与高度残差；
-- 使用 `0.05 m / 0.5 deg` 作为透明的归一化尺度，统计全局 RMS、改善对数和恶化对数。
-
-输出位于 `results/diagnostics/`。JSON 保存逐对结果，CSV 便于横向比较。
-
-## 接受规则
-
-局部扫描只用于定位，程序不会覆盖 `final_extrinsic_recommended.json`。候选至少需要满足：
-
-1. 不能只改善 Pair 0；全部精筛对的归一化 RMS 应下降；
-2. 改善的运动对数量应多于恶化数量；
-3. Open3D、small_gicp 与共识集合应给出相同方向的趋势；
-4. 地面法向和高度约束不能明显恶化；
-5. 多个代表性运动对的模式 4/5 可视化应同步改善。
-
-如果只有 Pair 0 改善，应把它视为局部配准或场景问题，不修改全局 X。
-
-对于当前仅含 yaw 的 RTK A，车体系 Z 轴平移在 AX=XB 中不可观。扫描程序会用 `X.z + 0.10 m` 做数值检查，但不会扫描或修改 z；z 必须由地面高度约束或外部量测确定。
diff --git a/README.md b/README.md
index d6b6d18..95ff8cf 100644
--- a/README.md
+++ b/README.md
@@ -1,226 +1,185 @@
-# LiDAR–双天线 RTK 手眼标定
+# 双天线RTK—3D LiDAR直接手眼标定
 
-本仓库提供一套可从原始 Medulla 记录复现的静态站点标定流程，求解三维激光雷达到后轮轴中心车体系的外参
+本仓库从静态站点原始数据复现 `T_RTK_lidar`：把原始雷达坐标转换到RTK导航坐标系。它**不是** `base_link` 车体外参，也不会在求解阶段使用车体航向偏置或RTK到后轮轴的XY杆臂。
+
+## 1. 输出坐标约定
+
+统一约定 `T_A_B` 把B系点变换到A系：
 
 ```text
-X = T_body_lidar
+p_RTK = T_RTK_lidar · p_lidar
 ```
 
-约定 `T_A_B` 将 B 系坐标变换到 A 系。对任意站点 i、j：
+RTK导航系在本仓库中定义为：
+
+- 原点：GGA位置参考点（通常为ANT1相位中心，必须结合接收机配置确认）；
+- X轴：`rawHeading`所表示的双天线基线在水平面的投影；
+- Y轴：左；
+- Z轴：上；
+- ENU航向：`yaw = 90° - rawHeading`；
+- roll、pitch：当前轨迹中固定为0。
+
+如果下游需要 `T_body_lidar`，必须另有经过确认的 `T_body_rtk`：
 
 ```text
-A_ij = T_W_Bi^-1 T_W_Bj       # RTK 给出的车体相对运动
-B_ij = T_Li_Lj                # GICP 给出的雷达相对运动
-A_ij X = X B_ij
+T_body_lidar = T_body_rtk · T_RTK_lidar
 ```
 
-当前部署建议仍采用 [results/01_previous_two_batches/final_extrinsic_deployment.json](results/01_previous_two_batches/final_extrinsic_deployment.json)。data4 是一次独立重算，结果与部署值相差约 `1.592 cm / 0.234°`，但自身 AX 残差更高，因此只作为候选和稳定性证据，不自动替换部署值。
+## 2. 算法流程
 
-## 标定总流程
-
-```mermaid
-flowchart LR
-  raw["原始站点 dlog / RTK、IMU rscap"] --> export["分别解析并统一到时间轴"]
-  export --> assoc["按每个 LiDAR 帧关联 RTK/IMU，导出 NPZ"]
-  assoc --> prep["每站选一帧，构建 RTK 车体位姿 A"]
-  prep --> b1["small_gicp 求 B"]
-  prep --> b2["Open3D GICP 求 B"]
-  b1 --> gate["与 X 无关的质量筛选及双后端一致性"]
-  b2 --> gate
-  gate --> solve["AX=XB + 地面约束求 X"]
-  solve --> check["残差、bootstrap、条件数、跨批复核和 3D 可视化"]
+```text
+逐站LiDAR dlog + RTK.rscap + IMU.rscap
+  → 分别解析并保留原始字段
+  → 以LiDAR帧时间为索引关联RTK/IMU，生成combined NPZ
+  → 每站选择一帧静态点云，GGA转局部ENU，rawHeading构造yaw-only RTK pose
+  → Open3D GICP和small_gicp分别求 B_ij = T_Li_Lj
+  → 留出点、Hessian、正反向、多初值和旋转共轭不变量筛选
+  → 两后端共同认可的边形成consensus B
+  → A_ij X = X B_ij + 地面法向/高度约束求 X = T_RTK_lidar
+  → bootstrap、双后端差异、逐对残差和3D可视化检查
 ```
 
-流程有两个原始数据入口：
+代码实际使用：
 
-- 旧式数据：LiDAR 和 `GPS-POST-Z` 位于每个站点 dlog 中，使用 `export_legacy_stations.ps1`。
-- 新式多传感器数据：LiDAR 位于逐站 dlog，RTK 与 IMU 是独立 `.rscap`，使用 `export_multisensor_stations.ps1`。处理顺序是统一时间轴、分别解析、按 LiDAR 帧关联、导出 NPZ。
+```text
+A_ij = inv(T_W_Ri) · T_W_Rj = T_Ri_Rj
+B_ij = T_Li_Lj              # 将站点j点云变换到站点i
+A_ij · X = X · B_ij
+X = T_RTK_lidar
+```
 
-IMU 会在新式数据中原样解析并随 LiDAR 帧关联保存，但当前 LiDAR–RTK 外参求解不使用 IMU，也不做运动畸变校正，因为每一站采集点云时车辆静止。IMU 外参应使用单独的激励数据和专用标定流程求解。
+## 3. 原始数据目录
 
-## 三批数据的角色
+大体积数据不提交Git。`DataRoot`下每个站点必须是一个独立dlog目录，至少包含：
 
-| 数据 | 原始格式 | 站点 | RTK 情况 | 在本仓库中的角色 |
-|---|---|---:|---|---|
-| 第一批 | 逐站 dlog，内嵌 GPS-POST-Z | 38 | 约 10 秒一条，部分站仅 1–11 个有效样本 | 辅助复核，不承担主要求解 |
-| 第二批 | 逐站 dlog，内嵌 GPS-POST-Z | 38 | 每站约 125–412 个有效样本，航向稳定 | 现部署外参的主要求解数据 |
-| data4 | 逐站 LiDAR dlog + 独立 RTK/IMU rscap | 34 | 11,678 个 LiDAR 帧均成功关联 fixed RTK、heading 和 IMU | 独立重算与跨批比较 |
+```text
+raw_dataset/
+├── stations/
+│   ├── 001/
+│   │   ├── dobject/
+│   │   └── dobject_recording/
+│   ├── 002/
+│   └── ...
+└── captures/
+    ├── rtk.rscap
+    └── imu.rscap
+```
 
-原始数据体积较大，不在 Git 仓库中。复现者应从云盘取得第一批、第二批或 data4 的原始目录，并在命令行传入路径。
+每个站点应在车辆完全静止后记录点云；建议不少于30站，并包含充足的直行、左转、右转和大角度转向姿态变化。
 
-## 环境
+## 4. 环境安装
 
-- Windows PowerShell 5.1 或 PowerShell 7
-- Python 3.10+
-- `pip install -r requirements.txt`
-- `small_gicp` 后端需要可导入 `small_gicp`；Open3D 后端需要 `open3d`
-
-所有脚本从自身位置推导仓库根目录。数据和输出路径均由参数传入，不依赖开发者电脑上的固定路径。
-
-## 从原始数据开始复现
-
-以下路径只表示格式，请替换为自己的目录。
-
-### A. 第一批、第二批旧式 dlog
+已验证环境为Windows、PowerShell、Python 3.11。安装依赖：
 
 ```powershell
-$Repo = "D:\你的代码目录\calibration"
-
-powershell.exe -NoProfile -ExecutionPolicy Bypass -File "$Repo\run\export_legacy_stations.ps1" `
-  -DataRoot "D:\你的数据目录\batch2_raw" `
-  -OutputRoot "D:\你的输出目录\batch2_export"
-
-powershell.exe -NoProfile -ExecutionPolicy Bypass -File "$Repo\run\prepare_legacy_dataset.ps1" `
-  -ExportRoot "D:\你的输出目录\batch2_export" `
-  -Output "D:\你的输出目录\batch2_prepared" `
-  -HeadingOffsetDeg 21.226 `
-  -AntennaLever -0.320,-0.365,0.620 `
-  -ExpectedStations 38 `
-  -HeadingStdLimitDeg 0.5
+python -m pip install -r requirements.txt
 ```
 
-第一批采用同一导出方式，但应在导出命令显式添加 `-RtkMaxDtMs 15000`；因其 RTK 稀疏，准备阶段也不建议沿用 `0.5°` 的严格站内航向离散度阈值。上述 `21.226°` 和杆臂 `[-0.320,-0.365,0.620] m` 是本项目已有两批数据采用的配置，不是通用常数；换车或改变天线安装后必须重新确认。
+依赖包括NumPy、SciPy、Open3D和small_gicp。若small_gicp没有对应Windows wheel，可在WSL2中安装后运行Python核心命令，或先只运行Open3D后端；完整共识流程需要两个后端都可用。
 
-### B. data4 式独立 RTK/IMU rscap
+## 5. 从原始数据一键复现
+
+在仓库根目录执行，路径由使用者通过参数传入，脚本内没有本机绝对路径：
 
 ```powershell
-powershell.exe -NoProfile -ExecutionPolicy Bypass -File "$Repo\run\export_multisensor_stations.ps1" `
-  -DataRoot "D:\你的数据目录\data4_raw" `
-  -RtkCapture "D:\你的数据目录\captures\rtk.rscap" `
-  -ImuCapture "D:\你的数据目录\captures\imu.rscap" `
-  -OutputRoot "D:\你的输出目录\data4_export"
+$Repo = (Resolve-Path ".").Path
+$Raw = "E:\calibration_data\data4"
+$Out = "E:\calibration_output\rtk_lidar"
 
-powershell.exe -NoProfile -ExecutionPolicy Bypass -File "$Repo\run\prepare_multisensor_dataset.ps1" `
-  -CombinedRoot "D:\你的输出目录\data4_export\combined" `
-  -Output "D:\你的输出目录\data4_prepared" `
-  -HeadingOffsetDeg 21.226 `
-  -AntennaLever -0.320,-0.365,0.620 `
+powershell.exe -NoProfile -ExecutionPolicy Bypass -File "$Repo\run\run_full_pipeline.ps1" `
+  -DataRoot "$Raw\stations" `
+  -RtkCapture "$Raw\captures\rtk.rscap" `
+  -ImuCapture "$Raw\captures\imu.rscap" `
+  -OutputRoot $Out `
+  -RtkReferenceHeightAboveGroundM 0.8535 `
   -ExpectedStations 34
 ```
 
-### C. 运行标定
-
-单批数据同时运行 small_gicp、Open3D GICP 和跨后端共识：
-
-```powershell
-powershell.exe -NoProfile -ExecutionPolicy Bypass -File "$Repo\run\run_single_dataset.ps1" `
-  -Prepared "D:\你的输出目录\data4_prepared" `
-  -OutputRoot "D:\你的输出目录\data4_calibration" `
-  -BodyHeight 0.2335
-```
-
-复现本仓库“第二批求解、第一批辅助复核”的历史流程：
-
-```powershell
-powershell.exe -NoProfile -ExecutionPolicy Bypass -File "$Repo\run\run_all.ps1" `
-  -Batch1Prepared "D:\你的输出目录\batch1_prepared" `
-  -Batch2Prepared "D:\你的输出目录\batch2_prepared" `
-  -OutputRoot "D:\你的输出目录\two_batch_calibration"
-```
-
-`BodyHeight=0.2335 m` 是后轮轴中心离地高度，用于把雷达地面平面约束转换到车体原点；它不是雷达离地高度。换轮胎、胎压或车体载荷后应重新测量并评估不确定度。
-
-## 如何判断结果
-
-不能仅凭 `AX=XB` 残差或一张叠图宣称外参正确。至少同时检查：
-
-1. B 的配准质量：收敛、有效对应点数/比例、RMSE、Hessian 信息矩阵特征值与条件数、small_gicp 与 Open3D 的相对运动一致性。
-2. X 的可观性：加权雅可比条件数越接近 1 越均衡；极大值说明存在弱方向，但没有脱离尺度和数据分布的单一硬阈值。本次 data4 为 `7.44`，不是病态。
-3. AX 残差分布：看 RMS、median、P90/P95、max 和逐对异常，而不是只看均值。
-4. 重采样稳定性：bootstrap 的六自由度标准差及置信区间。
-5. 跨批检查：同一 X 在独立批次的残差，以及两批独立求出的 X 之 SE(3) 差。
-6. 3D 可视化：模式 3 的 B 与模式 4 的 `X^-1 A X` 是否都使相同墙面、杆件和地面重合。
-
-当前没有把“增量小于某个值”当成绝对真值判据。工程筛查可先关注多数优质运动对是否约在厘米级到数厘米、亚度级；但阈值必须结合场景尺度、点云分辨率、RTK 质量和车辆运动幅度制定。模式 3 已错位时优先检查 B；模式 3 正常而模式 4 系统性错位时，再检查 A、坐标约定和 X。
-
-## 结果摘要
-
-| 结果 | 平移 xyz (m) | roll/pitch/yaw (deg) | AX 平移/旋转 RMS | 结论 |
-|---|---|---|---|---|
-| 部署值（第二批求解） | `[1.297760,-0.000067,0.720498]` | `[-0.785151,1.202661,-0.835510]` | `0.07985 m / 0.96118°`，39 对 | 当前建议部署 |
-| data4 独立候选 | `[1.300376,-0.001707,0.704877]` | `[-0.791892,1.393823,-0.970743]` | `0.11762 m / 1.24257°`，26 对 | 独立候选，不替换部署值 |
-
-data4 候选相对部署值变化 `1.592 cm / 0.234°`，其中 z 低 `1.562 cm`。旧部署值作用于 data4 的残差约 `0.11953 m / 1.24836°`；data4 候选作用于历史第二批的残差约 `0.07931 m / 0.98926°`。两个 X 的跨批表现接近，当前数据不足以证明 data4 的较低 z 更接近真值。
-
-## 仓库目录
+主要输出：
 
 ```text
-code/       标定、配准筛选、共识、比较和可视化核心程序
-tools/      原始 dlog/rscap 解析、时间关联、NPZ 导出和数据准备
-run/        不含本机固定路径的 PowerShell 入口
-results/    历史两批、data4 与跨批比较三个结果目录
+$Out/
+├── exported/
+│   ├── export/          # 各站LiDAR逐帧NPZ
+│   ├── parsed/          # RTK/IMU JSONL
+│   └── combined/        # 按LiDAR帧关联后的多传感器NPZ
+├── prepared_rtk_direct/
+│   ├── frames_all/      # 每站选中的静态帧
+│   └── reference_poses_rtk_gga_raw_heading.csv
+└── calibration/
+    ├── open3d_gicp/
+    ├── small_gicp/
+    ├── consensus/
+    ├── summary.json
+    └── final_T_RTK_lidar.json
 ```
 
-完整复现流程和所有主要文件职责均在本 README；`run/README.md`、`tools/README.md` 和 [results/README.md](results/README.md) 只是目录内快速索引。
+若已经有`combined/`，可跳过原始导出：
 
-## 代码、工具和运行入口职责
+```powershell
+powershell.exe -NoProfile -ExecutionPolicy Bypass -File "$Repo\run\run_direct_rtk_lidar.ps1" `
+  -CombinedRoot "E:\calibration_output\exported\combined" `
+  -WorkRoot "E:\calibration_output\prepared_rtk_direct" `
+  -OutputRoot "E:\calibration_output\calibration" `
+  -RtkReferenceHeightAboveGroundM 0.8535 `
+  -ExpectedStations 34
+```
 
-根 README 是本仓库唯一的完整复现说明。`run/README.md`、`tools/README.md` 和 `results/README.md` 只作为进入对应目录时的快速索引，不承载另一套流程。
+## 6. 3D可视化
 
-### code：标定核心
+```powershell
+powershell.exe -NoProfile -ExecutionPolicy Bypass -File "$Repo\run\view_result.ps1" `
+  -Frames "$Out\prepared_rtk_direct\frames_all" `
+  -Pairs "$Out\calibration\consensus\B_consensus.npz" `
+  -Extrinsic "$Out\calibration\final_T_RTK_lidar.json" `
+  -PairIndex 0
+```
 
-| 文件 | 职责 |
-|---|---|
-| `rigorous_calibration.py` | 核心 CLI。`ground` 拟合每站地面；`pairs` 用 small_gicp 或 Open3D GICP 求 B 和质量指标；`calibrate` 联合 AX=XB 与地面约束求 X；`validate` 计算指定 X 的逐对残差。 |
-| `refine_pairs.py` | 根据收敛、RMSE、对应关系、Hessian/信息矩阵和运动覆盖筛选 B；不读取 X，避免循环挑选。 |
-| `cross_backend_filter.py` | 对齐 Open3D 与 small_gicp 的同一站点对，只保留两个后端相互一致的 B。 |
-| `finalize_consensus.py` | 汇总历史两批的 consensus B、外参和第一批辅助复核。 |
-| `summarize_results.py` | 汇总两个后端的外参、B 质量和跨批检查，生成推荐结果。 |
-| `compare_extrinsics.py` | 在 SE(3) 上计算两套外参的严格相对平移和旋转差。 |
-| `visualize_pair_3d.py` | 交互显示原始点云、RTK A、GICP B、`X^-1AX`，并打印 `B^-1(X^-1AX)` 数值增量。 |
-| `scan_extrinsic_sensitivity.py` | 对 X 左乘小角度 roll/pitch/yaw 扰动，检查指定运动对的局部敏感方向。 |
+窗口中：
 
-### tools：原始数据到 prepared
+- 蓝色：目标站点i；橙色：站点j；
+- `1`：原始点云；
+- `2`：RTK运动A直接作为初值；
+- `3`：GICP测得的B；
+- `4`：最终外参预测的 `X^-1 A X`；
+- `Q/Esc`：退出。
 
-| 文件 | 职责 |
-|---|---|
-| `frontlidar_dlog_export.py` | 从 Medulla dlog 导出传感器坐标系 `points_raw`；旧格式可同时匹配站内 GPS-POST-Z。 |
-| `prepare_station_dataset.py` | 从旧式逐站导出中每站选择一帧，计算 yaw-only RTK 后轮轴位姿并生成 prepared。 |
-| `build_multisensor_npz.py` | 将独立 LiDAR、RTK、IMU 统一到 LiDAR 帧索引并生成 combined NPZ。 |
-| `prepare_multisensor_station_dataset.py` | 从 combined NPZ 选择每站静止帧，生成与旧流程相同的 prepared 接口。 |
-| `rscap_v2/capture_format_v2.py` | 读取 rscap v2 文件头、原始记录块和文件尾。 |
-| `rscap_v2/audit_capture_v2.py` | 审计 capture 完整性、时间范围和记录统计。 |
-| `rscap_v2/parse_rtk_imu_v2.py` | 分别解析 RTK 与 IMU capture，输出 JSONL。 |
-| `rscap_v2/pipeline_common*.py` | rscap 解析、时间处理和采集格式兼容的共用逻辑。 |
+模式3和4应让同一墙面、立柱、路缘和地面尽量重合。终端同时打印 `B^-1(X^-1AX)` 的平移和旋转增量。应查看多对，不能只挑视觉效果最好的一对。
 
-### run：推荐 PowerShell 入口
+## 7. data4参考结果
 
-| 文件 | 职责 |
-|---|---|
-| `export_legacy_stations.ps1` | 批量导出 LiDAR 与 RTK 同在逐站 dlog 中的旧格式。 |
-| `export_multisensor_stations.ps1` | 解析独立 RTK/IMU，导出逐站 LiDAR，并按 LiDAR 帧建立关联。 |
-| `prepare_legacy_dataset.ps1` | 旧式导出结果转换为 prepared。 |
-| `prepare_multisensor_dataset.ps1` | combined 多传感器结果转换为 prepared。 |
-| `run_single_dataset.ps1` | 单批数据同时完成两个 GICP 后端、B 筛选、consensus 和 X 求解。 |
-| `run_all.ps1` | 历史流程：第二批求解，第一批稀疏 RTK 数据作辅助复核。 |
-| `run_consensus_finish.ps1` | 在已有两个后端 B 的基础上重新生成 consensus 和汇总结果。 |
-| `run_sensitivity_scan.ps1` | 对历史运动对执行外参角度灵敏度扫描。 |
-| `view_result.ps1` | 传入匹配的 frames、B 和 X，运行交互式 3D 可视化。 |
-
-### 标定核心文件的数据关系
+仓库保留了精简参考产物，见[`results/reference_data4`](results/reference_data4/README.md)：
 
 ```text
-原始 dlog/rscap
-  -> tools 导出和时间关联
-  -> prepared/{frames_all, body_poses_*.csv}
-  -> rigorous_calibration.py pairs 生成 A、B
-  -> refine_pairs.py 做与 X 无关的 B 筛选
-  -> cross_backend_filter.py 生成 consensus B
-  -> rigorous_calibration.py calibrate 联合 AX=XB 与地面约束求 X
-  -> validate / visualize_pair_3d.py 做数值和三维检查
+translation_m = [1.638179350, -0.240844799, 0.084481236]
+RPY_deg_xyz   = [-0.817167459, 1.323288119, -22.104163318]
+
+站点：34
+共识运动对：25
+AX Translation RMS：0.100207 m
+AX Rotation RMS：1.252794°
+Weighted Jacobian condition：7.739413
+Open3D vs small_gicp：0.003889 m / 0.188431°
 ```
 
+唯一建议下游读取的参考结果是[`final_T_RTK_lidar.json`](results/reference_data4/final_T_RTK_lidar.json)。
 
-## 重要限制
+## 8. z与精度限制
 
-- RTK 车体姿态当前是双天线 heading 构造的 yaw-only 轨迹；没有用 RTK pitch/roll 构造 A。
-- 新式解析器保存 IMU 与 RTK pitch 等原始字段，但当前手眼方程未融合 IMU。
-- 静止站点法不估计 LiDAR–RTK 时间偏移；时间戳关联必须在导出阶段通过审计。
-- 地面约束负责 roll、pitch 和 z 的补充可观性，不会独立求出另一套六自由度外参。
-- 仓库归档的是结果和轻量 B 文件，不包含云盘中的原始点云数据。
+平面阿克曼运动不能独立观测z。参考结果使用34站地面平面和RTK参考点离地`0.8535 m`约束z；该高度必须量到实际GGA参考点/天线相位中心。更改参考高度后必须重新求解。
 
-## 专题说明
+AX残差、Hessian/Jacobian条件数、bootstrap和双后端一致性只证明内部一致性，不能单独证明逐帧GT达到±3 cm。当前关联仍以LiDAR和串口主机接收时间为主；GNSS周/周内时间和IMU设备时间被保留，但没有联合估计时钟偏移与漂移。用于连续GT pose前，应补做严格设备时间同步和独立轨迹验证。
 
-- [运动对诊断](PAIR_DIAGNOSTICS.md)
-- [双后端共识筛选](CONSENSUS_SELECTION.md)
-- [结果文件索引](results/README.md)
+此外，代码无法单独证明GGA对应哪根物理天线、`rawHeading`是ANT1→ANT2还是ANT2→ANT1；必须用接收机配置、接线和现场运动实验确认。方向错误会导致RTK坐标系yaw相差约180°。
+
+## 9. 仓库目录
+
+| 目录 | 职责 |
+|---|---|
+| [`code/`](code/) | GICP、运动对质量评价、AX=XB求解、结果封装和3D可视化 |
+| [`tools/`](tools/) | 原始dlog/rscap解析、按LiDAR帧关联及静态站点prepared生成 |
+| [`run/`](run/) | PowerShell入口；所有数据和输出路径都通过参数传入 |
+| [`results/reference_data4/`](results/reference_data4/) | 可提交Git的精简参考结果，不包含点云和本机过程目录 |
+| `work/`、`outputs/` | 本地运行生成物，已由`.gitignore`排除 |
+
+各代码文件职责见[`code/README.md`](code/README.md)，命令索引见[`run/README.md`](run/README.md)，工具说明见[`tools/README.md`](tools/README.md)。
diff --git a/LiDAR_RTK_Direct_Calibration/code/README.md b/code/README.md
similarity index 100%
rename from LiDAR_RTK_Direct_Calibration/code/README.md
rename to code/README.md
diff --git a/code/compare_extrinsics.py b/code/compare_extrinsics.py
index 4e8ca80..b407738 100644
--- a/code/compare_extrinsics.py
+++ b/code/compare_extrinsics.py
@@ -1,5 +1,5 @@
 #!/usr/bin/env python3
-"""Compare two T_body_lidar JSON files in parameter space and on SE(3)."""
+"""Compare two homogeneous-extrinsic JSON files in parameter space and on SE(3)."""
 
 import argparse
 import json
diff --git a/code/finalize_consensus.py b/code/finalize_consensus.py
deleted file mode 100644
index c38f037..0000000
--- a/code/finalize_consensus.py
+++ /dev/null
@@ -1,58 +0,0 @@
-#!/usr/bin/env python3
-"""Publish the cross-backend-consensus result as the recommended deliverable."""
-import argparse
-import json
-from pathlib import Path
-
-
-def main():
-    parser = argparse.ArgumentParser(description=__doc__)
-    parser.add_argument("--consensus-extrinsic", required=True)
-    parser.add_argument("--consensus-check", required=True)
-    parser.add_argument("--open3d-extrinsic", required=True)
-    parser.add_argument("--small-extrinsic", required=True)
-    parser.add_argument("--output", required=True)
-    parser.add_argument("--summary", required=True)
-    args = parser.parse_args()
-    consensus = json.loads(Path(args.consensus_extrinsic).read_text(encoding="utf-8-sig"))
-    check = json.loads(Path(args.consensus_check).read_text(encoding="utf-8-sig"))
-    open3d = json.loads(Path(args.open3d_extrinsic).read_text(encoding="utf-8-sig"))
-    small = json.loads(Path(args.small_extrinsic).read_text(encoding="utf-8-sig"))
-    summary = {
-        "recommended_method": "Open3D B gated by Open3D-small_gicp cross-backend agreement",
-        "selection_is_X_independent": True,
-        "second_batch_role": "estimation (dense RTK)",
-        "first_batch_role": "auxiliary check only (sparse RTK)",
-        "consensus": {
-            "translation_m": consensus["translation_m"],
-            "rotation_rpy_deg_xyz": consensus["rotation_rpy_deg_xyz"],
-            "estimation": consensus["estimation"]["residuals"],
-            "bootstrap_std": consensus["bootstrap"]["std"],
-            "batch1_auxiliary": check["metrics"],
-        },
-        "separate_backend_results": {
-            "open3d_gicp": {
-                "translation_m": open3d["translation_m"],
-                "rotation_rpy_deg_xyz": open3d["rotation_rpy_deg_xyz"],
-            },
-            "small_gicp": {
-                "translation_m": small["translation_m"],
-                "rotation_rpy_deg_xyz": small["rotation_rpy_deg_xyz"],
-            },
-        },
-        "warning": "AX rotation RMS remains about one degree; this is not centimetre-grade absolute certification.",
-    }
-    published = dict(consensus)
-    published["selection"] = {
-        "method": summary["recommended_method"],
-        "selection_is_X_independent": True,
-        "consensus_pair_threshold": "Open3D-small_gicp B delta <= 0.05 m and <= 0.50 deg",
-        "warning": summary["warning"],
-    }
-    Path(args.output).write_text(json.dumps(published, ensure_ascii=False, indent=2), encoding="utf-8")
-    Path(args.summary).write_text(json.dumps(summary, ensure_ascii=False, indent=2), encoding="utf-8")
-    print(json.dumps(summary, ensure_ascii=False, indent=2))
-
-
-if __name__ == "__main__":
-    main()
diff --git a/LiDAR_RTK_Direct_Calibration/code/finalize_direct_rtk_lidar.py b/code/finalize_direct_rtk_lidar.py
similarity index 100%
rename from LiDAR_RTK_Direct_Calibration/code/finalize_direct_rtk_lidar.py
rename to code/finalize_direct_rtk_lidar.py
diff --git a/code/rigorous_calibration.py b/code/rigorous_calibration.py
index 4732b0d..0974795 100644
--- a/code/rigorous_calibration.py
+++ b/code/rigorous_calibration.py
@@ -1,8 +1,9 @@
 #!/usr/bin/env python3
-"""Rigorous stationary LiDAR / dual-antenna RTK hand-eye calibration.
+"""Rigorous stationary LiDAR / reference-trajectory hand-eye calibration.
 
 Convention: T_A_B maps points from frame B into frame A.
-X = T_body_lidar, A_ij = T_W_Bi^-1 T_W_Bj, B_ij = T_Li_Lj,
+For this repository the reference frame is the RTK navigation frame.
+X = T_RTK_lidar, A_ij = T_W_Ri^-1 T_W_Rj, B_ij = T_Li_Lj,
 therefore A_ij X = X B_ij. Raw sensor-frame points_raw are used.
 """
 from __future__ import annotations
@@ -367,17 +368,17 @@ def cmd_pairs(args):
     stations = load_stations(
         args.frames, args.min_range, args.max_range, args.z_min, args.z_max
     )
-    body = read_poses(args.body)
+    reference = read_poses(args.reference_poses)
     if len(stations) < args.min_stations:
         raise ValueError(f"need at least {args.min_stations} stations, got {len(stations)}")
-    body_poses, body_dt = [], []
+    reference_poses, reference_dt = [], []
     for timestamp, _, _, xyz in stations:
         if len(xyz) < args.min_roi_points:
             raise ValueError(f"station at {timestamp} has only {len(xyz)} ROI points")
-        pose, dt = nearest_pose(body, timestamp + args.time_offset)
-        body_poses.append(pose)
-        body_dt.append(dt)
-    body_poses = np.asarray(body_poses)
+        pose, dt = nearest_pose(reference, timestamp + args.time_offset)
+        reference_poses.append(pose)
+        reference_dt.append(dt)
+    reference_poses = np.asarray(reference_poses)
     split = [split_holdout(station[3], args.holdout_fraction, i)
              for i, station in enumerate(stations)]
     rng = np.random.default_rng(args.seed)
@@ -385,7 +386,7 @@ def cmd_pairs(args):
     accepted_transforms = {}
     for i in range(len(stations)):
         for j in range(i + args.min_gap, min(len(stations), i + args.max_gap + 1)):
-            a_ij = inverse_transform(body_poses[i]) @ body_poses[j]
+            a_ij = inverse_transform(reference_poses[i]) @ reference_poses[j]
             translation = float(np.linalg.norm(a_ij[:2, 3]))
             rotation = rotation_angle_deg(a_ij[:3, :3])
             if translation < args.min_translation and rotation < args.min_rotation:
@@ -445,7 +446,7 @@ def cmd_pairs(args):
                 "lidar_time_i": stations[i][0], "lidar_time_j": stations[j][0],
                 "frame_counter_i": stations[i][1], "frame_counter_j": stations[j][1],
                 "rtk_translation_m": translation, "rtk_rotation_deg": rotation,
-                "nearest_rtk_dt_i_s": body_dt[i], "nearest_rtk_dt_j_s": body_dt[j],
+                "nearest_rtk_dt_i_s": reference_dt[i], "nearest_rtk_dt_j_s": reference_dt[j],
                 "initial_B_source": "X0=identity; B0=A (no measured extrinsic)",
                 "B_ij_4x4": forward["transform"].tolist(),
                 "backend": args.backend, "backend_converged": forward["converged"],
@@ -474,7 +475,7 @@ def cmd_pairs(args):
         output, A=np.asarray(accepted_a), B=np.asarray(accepted_b),
         meta=np.asarray(accepted_meta),
         station_times=np.asarray([item[0] for item in stations]),
-        rtk_nearest_dt_s=np.asarray(body_dt), backend=np.asarray(args.backend),
+        rtk_nearest_dt_s=np.asarray(reference_dt), backend=np.asarray(args.backend),
     )
     quality = {
         "schema_version": 2,
@@ -556,7 +557,7 @@ def calibration_residual(params, a_array, b_array, planes, args):
         normal_body = x[:3, :3] @ plane[:3]
         values.extend((np.cross(normal_body, body_up) / args.plane_normal_sigma).tolist())
         body_distance = plane[3] - float(normal_body @ x[:3, 3])
-        values.append((body_distance - args.body_height) / args.plane_height_sigma)
+        values.append((body_distance - args.reference_height) / args.plane_height_sigma)
     return np.asarray(values)
 
 
@@ -644,7 +645,7 @@ def cmd_calibrate(args):
         "schema_version": 2,
         "success": bool(best.success),
         "message": best.message,
-        "convention": "T_body_lidar maps raw LiDAR points into rear-axle body frame",
+        "convention": "T_reference_lidar maps raw LiDAR points into the supplied reference frame",
         "equation": "A_ij X = X B_ij",
         "measured_extrinsic_used_as_initial": False,
         "translation_m": x[:3, 3].tolist(),
@@ -655,8 +656,8 @@ def cmd_calibrate(args):
                        "residuals": pair_metrics(a_array, b_array, x)},
         "ground": {
             "planes": len(planes),
-            "body_origin_height_above_ground_m": args.body_height,
-            "formula": "d_lidar - (R_X n_lidar)^T t_X - body_height",
+            "reference_origin_height_above_ground_m": args.reference_height,
+            "formula": "d_lidar - (R_X n_lidar)^T t_X - reference_height",
         },
         "linearized_one_sigma": {
             "translation_m": sigma[:3].tolist(),
@@ -713,7 +714,8 @@ def build_parser():
 
     pairs = commands.add_parser("pairs")
     pairs.add_argument("--backend", choices=["open3d", "small_gicp"], required=True)
-    pairs.add_argument("--frames", required=True); pairs.add_argument("--body", required=True)
+    pairs.add_argument("--frames", required=True)
+    pairs.add_argument("--reference-poses", "--body", dest="reference_poses", required=True)
     pairs.add_argument("--output", required=True); pairs.add_argument("--quality-json"); pairs.add_argument("--quality-csv")
     pairs.add_argument("--time-offset", type=float, default=0.0)
     pairs.add_argument("--min-stations", type=int, default=30); pairs.add_argument("--min-pairs", type=int, default=25)
@@ -746,7 +748,7 @@ def build_parser():
     calibrate.add_argument("--rotation-sigma", type=float, default=0.5)
     calibrate.add_argument("--plane-normal-sigma", type=float, default=0.02)
     calibrate.add_argument("--plane-height-sigma", type=float, default=0.03)
-    calibrate.add_argument("--body-height", type=float, default=0.2335)
+    calibrate.add_argument("--reference-height", "--body-height", dest="reference_height", type=float, default=0.8535)
     calibrate.add_argument("--solver-multistart", type=int, default=12)
     calibrate.add_argument("--start-translation-sigma", type=float, default=1.0)
     calibrate.add_argument("--start-rotation-sigma", type=float, default=20.0)
diff --git a/code/scan_extrinsic_sensitivity.py b/code/scan_extrinsic_sensitivity.py
deleted file mode 100644
index d277d64..0000000
--- a/code/scan_extrinsic_sensitivity.py
+++ /dev/null
@@ -1,311 +0,0 @@
-#!/usr/bin/env python3
-"""Scan body-left RPY corrections locally and validate them over every B pair.
-
-This command is diagnostic only.  It never writes or replaces an extrinsic JSON.
-"""
-from __future__ import annotations
-
-import argparse
-import csv
-import json
-import math
-from pathlib import Path
-
-import numpy as np
-from scipy.spatial.transform import Rotation
-
-from rigorous_calibration import (
-    inverse_transform, read_pairs, read_planes, rotation_angle_deg, rpy_deg,
-)
-
-
-def statistics(values):
-    values = np.asarray(values, float)
-    return {
-        "rms": float(np.sqrt(np.mean(values ** 2))),
-        "median": float(np.median(values)),
-        "p90": float(np.quantile(values, 0.90)),
-        "p95": float(np.quantile(values, 0.95)),
-        "max": float(np.max(values)),
-    }
-
-
-def body_left_rpy(x, rpy_correction_deg):
-    correction = np.eye(4)
-    correction[:3, :3] = Rotation.from_euler(
-        "xyz", np.asarray(rpy_correction_deg, float), degrees=True
-    ).as_matrix()
-    return correction @ x
-
-
-def pair_delta(a_ij, b_ij, x):
-    predicted = inverse_transform(x) @ a_ij @ x
-    delta = inverse_transform(b_ij) @ predicted
-    translation = np.asarray(delta[:3, 3], float)
-    return {
-        "translation_xyz_m": translation.tolist(),
-        "translation_xyz_cm": (100.0 * translation).tolist(),
-        "translation_norm_m": float(np.linalg.norm(translation)),
-        "rotation_rpy_deg_xyz": rpy_deg(delta[:3, :3]),
-        "rotation_angle_deg": rotation_angle_deg(delta[:3, :3]),
-    }
-
-
-def ground_metrics(planes, x, body_height):
-    if len(planes) == 0:
-        return None
-    up = np.array([0.0, 0.0, 1.0])
-    tilt_deg, height_m = [], []
-    for plane in planes:
-        normal_body = x[:3, :3] @ plane[:3]
-        normal_body /= np.linalg.norm(normal_body)
-        tilt_deg.append(math.degrees(math.atan2(
-            np.linalg.norm(np.cross(normal_body, up)),
-            float(np.clip(normal_body @ up, -1.0, 1.0)),
-        )))
-        height_m.append(
-            float(plane[3] - normal_body @ x[:3, 3] - body_height)
-        )
-    return {
-        "normal_tilt_deg": statistics(tilt_deg),
-        "height_residual_m": statistics(height_m),
-    }
-
-
-def evaluate(label, correction, a_array, b_array, meta, x, pair_index,
-             translation_scale, rotation_scale, planes, body_height):
-    candidate_x = body_left_rpy(x, correction)
-    per_pair = []
-    translation, rotation, normalized = [], [], []
-    for index, (a_ij, b_ij, pair_meta) in enumerate(zip(a_array, b_array, meta)):
-        item = pair_delta(a_ij, b_ij, candidate_x)
-        item.update({
-            "pair_index": index,
-            "i": int(pair_meta[0]),
-            "j": int(pair_meta[1]),
-        })
-        t = item["translation_norm_m"]
-        r = item["rotation_angle_deg"]
-        translation.append(t)
-        rotation.append(r)
-        normalized.append(math.hypot(t / translation_scale, r / rotation_scale))
-        per_pair.append(item)
-    return {
-        "label": label,
-        "body_left_rpy_correction_deg_xyz": list(map(float, correction)),
-        "candidate_extrinsic": {
-            "translation_m": candidate_x[:3, 3].tolist(),
-            "rotation_rpy_deg_xyz": rpy_deg(candidate_x[:3, :3]),
-        },
-        "all_pairs": {
-            "count": len(per_pair),
-            "translation_m": statistics(translation),
-            "rotation_deg": statistics(rotation),
-            "normalized_pair_score": statistics(normalized),
-            "normalized_global_rms": float(np.sqrt(np.mean(np.asarray(normalized) ** 2))),
-        },
-        "selected_pair": per_pair[pair_index],
-        "ground": ground_metrics(planes, candidate_x, body_height),
-        "per_pair": per_pair,
-    }
-
-
-def candidate_grid(pitch_values, roll_values, yaw_values):
-    answer = [("baseline", (0.0, 0.0, 0.0))]
-    for pitch in pitch_values:
-        answer.append((f"pitch_{pitch:+.3f}", (0.0, pitch, 0.0)))
-    for pitch in (0.0, *pitch_values):
-        for roll in roll_values:
-            answer.append((
-                f"pitch_{pitch:+.3f}_roll_{roll:+.3f}",
-                (roll, pitch, 0.0),
-            ))
-    for yaw in yaw_values:
-        answer.append((f"yaw_{yaw:+.3f}_diagnostic", (0.0, 0.0, yaw)))
-    unique = []
-    seen = set()
-    for label, values in answer:
-        key = tuple(round(float(value), 12) for value in values)
-        if key not in seen:
-            seen.add(key)
-            unique.append((label, values))
-    return unique
-
-
-def z_observability(a_array, x, test_shift_m):
-    shift = np.eye(4)
-    shift[2, 3] = test_shift_m
-    shifted_x = shift @ x
-    effects = []
-    for a_ij in a_array:
-        before = inverse_transform(x) @ a_ij @ x
-        after = inverse_transform(shifted_x) @ a_ij @ shifted_x
-        delta = inverse_transform(before) @ after
-        effects.append((
-            float(np.linalg.norm(delta[:3, 3])),
-            rotation_angle_deg(delta[:3, :3]),
-        ))
-    effects = np.asarray(effects, float)
-    maximum = np.max(effects, axis=0)
-    return {
-        "body_left_z_test_shift_m": test_shift_m,
-        "max_predicted_motion_change_translation_m": float(maximum[0]),
-        "max_predicted_motion_change_rotation_deg": float(maximum[1]),
-        "numerically_unobservable": bool(maximum[0] < 1e-10 and maximum[1] < 1e-10),
-        "note": "AX pairs cannot determine X.z when every A rotation preserves body Z; use ground/external height constraints.",
-    }
-
-
-def main():
-    parser = argparse.ArgumentParser(description=__doc__)
-    parser.add_argument("--pairs", required=True)
-    parser.add_argument("--extrinsic", required=True)
-    parser.add_argument("--output", required=True)
-    parser.add_argument("--csv")
-    parser.add_argument("--ground-planes")
-    parser.add_argument("--pair-index", type=int, default=0)
-    parser.add_argument("--pitch-values", nargs="+", type=float, default=[0.1, 0.2, 0.3])
-    parser.add_argument("--roll-values", nargs="+", type=float, default=[-0.2, -0.1, 0.1])
-    parser.add_argument("--yaw-values", nargs="+", type=float, default=[-0.2, 0.2])
-    parser.add_argument("--translation-scale", type=float, default=0.05)
-    parser.add_argument("--rotation-scale", type=float, default=0.5)
-    parser.add_argument("--body-height", type=float, default=0.2335)
-    args = parser.parse_args()
-
-    a_array, b_array, meta, stations = read_pairs(args.pairs)
-    if not 0 <= args.pair_index < len(a_array):
-        raise IndexError(f"pair-index {args.pair_index} outside [0,{len(a_array)-1}]")
-    with Path(args.extrinsic).open(encoding="utf-8-sig") as stream:
-        x = np.asarray(json.load(stream)["matrix_4x4"], float)
-    planes = read_planes(args.ground_planes) if args.ground_planes else np.empty((0, 4))
-
-    candidates = [
-        evaluate(
-            label, correction, a_array, b_array, meta, x, args.pair_index,
-            args.translation_scale, args.rotation_scale, planes, args.body_height,
-        )
-        for label, correction in candidate_grid(
-            args.pitch_values, args.roll_values, args.yaw_values
-        )
-    ]
-    baseline = candidates[0]
-    baseline_scores = np.asarray([
-        math.hypot(
-            item["translation_norm_m"] / args.translation_scale,
-            item["rotation_angle_deg"] / args.rotation_scale,
-        )
-        for item in baseline["per_pair"]
-    ])
-    base_global = baseline["all_pairs"]["normalized_global_rms"]
-    for candidate in candidates:
-        scores = np.asarray([
-            math.hypot(
-                item["translation_norm_m"] / args.translation_scale,
-                item["rotation_angle_deg"] / args.rotation_scale,
-            )
-            for item in candidate["per_pair"]
-        ])
-        delta = scores - baseline_scores
-        candidate["comparison_to_baseline"] = {
-            "normalized_global_rms_change": float(
-                candidate["all_pairs"]["normalized_global_rms"] - base_global
-            ),
-            "improved_pairs": int(np.sum(delta < -1e-12)),
-            "worsened_pairs": int(np.sum(delta > 1e-12)),
-            "unchanged_pairs": int(np.sum(np.abs(delta) <= 1e-12)),
-            "median_per_pair_score_change": float(np.median(delta)),
-            "global_consistency_signal": bool(
-                candidate["all_pairs"]["normalized_global_rms"] < base_global
-                and np.sum(delta < -1e-12) > np.sum(delta > 1e-12)
-            ),
-        }
-
-    ranking = sorted(
-        candidates,
-        key=lambda item: item["all_pairs"]["normalized_global_rms"],
-    )
-    report = {
-        "schema_version": 1,
-        "diagnostic_only": True,
-        "extrinsic_was_modified": False,
-        "equation": "delta_ij = B_ij^-1 * (X^-1 * A_ij * X)",
-        "correction_convention": "X_test = DeltaR_body * X; DeltaR uses fixed body xyz RPY axes",
-        "component_frame": "delta translation/RPY components are in station-j LiDAR coordinates, not screen axes",
-        "selection_rule": (
-            "Never accept a correction from selected_pair alone. Require improvement over all "
-            "refined pairs, directional consistency across pairs, acceptable ground constraints, "
-            "and independent visual review. This script never overwrites X."
-        ),
-        "pairs_file": str(Path(args.pairs).resolve()),
-        "extrinsic_file": str(Path(args.extrinsic).resolve()),
-        "stations": stations,
-        "pairs": len(a_array),
-        "selected_pair_index": args.pair_index,
-        "selected_pair_stations": [int(meta[args.pair_index, 0]), int(meta[args.pair_index, 1])],
-        "normalization": {
-            "translation_scale_m": args.translation_scale,
-            "rotation_scale_deg": args.rotation_scale,
-        },
-        "z_observability": z_observability(a_array, x, 0.10),
-        "ranking_by_all_pair_normalized_rms": [
-            {
-                "rank": rank,
-                "label": item["label"],
-                "body_left_rpy_correction_deg_xyz": item["body_left_rpy_correction_deg_xyz"],
-                "normalized_global_rms": item["all_pairs"]["normalized_global_rms"],
-                **item["comparison_to_baseline"],
-            }
-            for rank, item in enumerate(ranking, 1)
-        ],
-        "candidates": candidates,
-    }
-
-    output = Path(args.output)
-    output.parent.mkdir(parents=True, exist_ok=True)
-    output.write_text(json.dumps(report, ensure_ascii=False, indent=2), encoding="utf-8")
-    csv_path = Path(args.csv) if args.csv else output.with_suffix(".csv")
-    with csv_path.open("w", encoding="utf-8", newline="") as stream:
-        fields = [
-            "label", "roll_correction_deg", "pitch_correction_deg", "yaw_correction_deg",
-            "selected_pair_translation_cm", "selected_pair_rotation_deg",
-            "all_pair_translation_rms_m", "all_pair_rotation_rms_deg",
-            "normalized_global_rms", "normalized_global_rms_change",
-            "improved_pairs", "worsened_pairs", "global_consistency_signal",
-            "ground_normal_tilt_rms_deg", "ground_height_rms_m",
-        ]
-        writer = csv.DictWriter(stream, fieldnames=fields)
-        writer.writeheader()
-        for item in candidates:
-            correction = item["body_left_rpy_correction_deg_xyz"]
-            ground = item["ground"]
-            comparison = item["comparison_to_baseline"]
-            writer.writerow({
-                "label": item["label"],
-                "roll_correction_deg": correction[0],
-                "pitch_correction_deg": correction[1],
-                "yaw_correction_deg": correction[2],
-                "selected_pair_translation_cm": item["selected_pair"]["translation_norm_m"] * 100.0,
-                "selected_pair_rotation_deg": item["selected_pair"]["rotation_angle_deg"],
-                "all_pair_translation_rms_m": item["all_pairs"]["translation_m"]["rms"],
-                "all_pair_rotation_rms_deg": item["all_pairs"]["rotation_deg"]["rms"],
-                "normalized_global_rms": item["all_pairs"]["normalized_global_rms"],
-                "normalized_global_rms_change": comparison["normalized_global_rms_change"],
-                "improved_pairs": comparison["improved_pairs"],
-                "worsened_pairs": comparison["worsened_pairs"],
-                "global_consistency_signal": comparison["global_consistency_signal"],
-                "ground_normal_tilt_rms_deg": None if ground is None else ground["normal_tilt_deg"]["rms"],
-                "ground_height_rms_m": None if ground is None else ground["height_residual_m"]["rms"],
-            })
-
-    print(json.dumps({
-        "diagnostic_only": True,
-        "selected_pair": baseline["selected_pair"],
-        "z_observability": report["z_observability"],
-        "top_all_pair_candidates": report["ranking_by_all_pair_normalized_rms"][:8],
-        "output": str(output.resolve()),
-        "csv": str(csv_path.resolve()),
-    }, ensure_ascii=False, indent=2))
-
-
-if __name__ == "__main__":
-    main()
diff --git a/code/summarize_results.py b/code/summarize_results.py
deleted file mode 100644
index acde29d..0000000
--- a/code/summarize_results.py
+++ /dev/null
@@ -1,87 +0,0 @@
-#!/usr/bin/env python3
-"""Build a concise backend comparison and select the recommended result."""
-import argparse
-import json
-from pathlib import Path
-
-import numpy as np
-from scipy.spatial.transform import Rotation
-
-
-def main():
-    parser = argparse.ArgumentParser(description=__doc__)
-    parser.add_argument("--open3d", required=True)
-    parser.add_argument("--small", required=True)
-    parser.add_argument("--open3d-quality", required=True)
-    parser.add_argument("--small-quality", required=True)
-    parser.add_argument("--open3d-check", required=True)
-    parser.add_argument("--small-check", required=True)
-    parser.add_argument("--output", required=True)
-    parser.add_argument("--recommended-output", required=True)
-    args = parser.parse_args()
-
-    open_result = json.loads(Path(args.open3d).read_text(encoding="utf-8-sig"))
-    small_result = json.loads(Path(args.small).read_text(encoding="utf-8-sig"))
-    open_quality = json.loads(Path(args.open3d_quality).read_text(encoding="utf-8-sig"))
-    small_quality = json.loads(Path(args.small_quality).read_text(encoding="utf-8-sig"))
-    open_check = json.loads(Path(args.open3d_check).read_text(encoding="utf-8-sig"))
-    small_check = json.loads(Path(args.small_check).read_text(encoding="utf-8-sig"))
-    x_open = np.asarray(open_result["matrix_4x4"], float)
-    x_small = np.asarray(small_result["matrix_4x4"], float)
-    delta = np.linalg.inv(x_open) @ x_small
-
-    def compact(result, quality, check):
-        estimate = result["estimation"]["residuals"]
-        auxiliary = check["metrics"]
-        return {
-            "translation_m": result["translation_m"],
-            "rotation_rpy_deg_xyz": result["rotation_rpy_deg_xyz"],
-            "estimation_pairs": estimate["pairs"],
-            "estimation_translation_rms_m": estimate["translation_m"]["rms"],
-            "estimation_rotation_rms_deg": estimate["rotation_deg"]["rms"],
-            "bootstrap_std": result["bootstrap"]["std"],
-            "initial_B_loop_closure": quality["accepted_loop_closure"],
-            "batch1_auxiliary_pairs": auxiliary["pairs"],
-            "batch1_auxiliary_translation_rms_m": auxiliary["translation_m"]["rms"],
-            "batch1_auxiliary_rotation_rms_deg": auxiliary["rotation_deg"]["rms"],
-        }
-
-    summary = {
-        "recommended_backend": "open3d_gicp",
-        "selection_reason": (
-            "The two X estimates agree closely; Open3D has lower second-batch AX residual, "
-            "better B loop closure, and lower first-batch auxiliary residual."
-        ),
-        "coordinate_convention": "T_body_lidar maps raw LiDAR points into rear-axle body frame",
-        "measured_extrinsic_used_as_initial": False,
-        "second_batch_role": "estimation (dense RTK)",
-        "first_batch_role": "auxiliary check only (sparse RTK)",
-        "backend_difference": {
-            "translation_m": float(np.linalg.norm(delta[:3, 3])),
-            "rotation_deg": float(np.rad2deg(Rotation.from_matrix(delta[:3, :3]).magnitude())),
-        },
-        "open3d_gicp": compact(open_result, open_quality, open_check),
-        "small_gicp": compact(small_result, small_quality, small_check),
-        "important_limit": (
-            "Backend agreement is strong, but AX rotation RMS remains about one degree. "
-            "This is not a centimetre-grade absolute certification."
-        ),
-    }
-    output = Path(args.output)
-    output.parent.mkdir(parents=True, exist_ok=True)
-    output.write_text(json.dumps(summary, ensure_ascii=False, indent=2), encoding="utf-8")
-    recommended = dict(open_result)
-    recommended["selection"] = {
-        "recommended_backend": "open3d_gicp",
-        "comparison_summary": str(output.name),
-        "backend_difference": summary["backend_difference"],
-        "warning": summary["important_limit"],
-    }
-    Path(args.recommended_output).write_text(
-        json.dumps(recommended, ensure_ascii=False, indent=2), encoding="utf-8"
-    )
-    print(json.dumps(summary, ensure_ascii=False, indent=2))
-
-
-if __name__ == "__main__":
-    main()
diff --git a/LiDAR_RTK_Direct_Calibration/data/README.md b/data/README.md
similarity index 100%
rename from LiDAR_RTK_Direct_Calibration/data/README.md
rename to data/README.md
diff --git a/requirements.txt b/requirements.txt
index 36d6239..9f8e5e8 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -1,4 +1,4 @@
 numpy>=1.26
 scipy>=1.11
 open3d>=0.18
-small-gicp==1.0.1
+small-gicp
diff --git a/results/01_previous_two_batches/README.md b/results/01_previous_two_batches/README.md
deleted file mode 100644
index 7983064..0000000
--- a/results/01_previous_two_batches/README.md
+++ /dev/null
@@ -1,10 +0,0 @@
-# 历史两批结果
-
-第二批 38 站的密集 RTK 数据用于求解；第一批 38 站因 RTK 约 10 秒一条，仅作辅助检查。最终部署值：
-
-```text
-translation_m = [1.297759692, -0.000067331, 0.720497835]
-RPY_deg_xyz   = [-0.785151146, 1.202660822, -0.835510053]
-```
-
-共识估计使用 39 个运动对，AX RMS 约 `0.07985 m / 0.96118°`。第一批辅助检查 22 对约 `0.06067 m / 1.00298°`。`final_extrinsic_deployment.json` 是唯一建议直接交给下游的部署 JSON；其余文件用于审计和复现。
diff --git a/results/01_previous_two_batches/common/ground_planes_batch2.csv b/results/01_previous_two_batches/common/ground_planes_batch2.csv
deleted file mode 100644
index 9d84bc2..0000000
--- a/results/01_previous_two_batches/common/ground_planes_batch2.csv
+++ /dev/null
@@ -1,39 +0,0 @@
-time,nx,ny,nz,d,inliers,rms_m,frame_counter
-1784279335.9505181,-0.05361540190749781,-0.028612066826359885,0.9981516609765378,0.9970438972044271,1413,0.014218123000381944,190
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-1784279517.5427606,-0.025255763366701406,-0.019499239847777874,0.9994908334057517,0.9627800728846587,1377,0.013484126577744504,2006
-1784279605.2394407,-0.01384716564355861,-0.022470612380854543,0.9996516031012351,0.9522772824995122,1451,0.012466425277627606,2883
-1784279701.2360666,-0.01555857544224011,-0.0217686215576034,0.999641964828253,0.9563364194973247,1538,0.012300341594741273,3843
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-1784281027.8795433,-0.018194511282557984,-0.007436316920549397,0.9998068118140855,0.9473391457135313,994,0.013690484345080097,3477
-1784281119.375541,-0.031030924482729524,-0.005127874296086657,0.9995052709370525,0.9424388693848053,1050,0.012540091408749102,4392
-1784281219.2718523,0.010887801537886658,0.029801594631508527,0.9994965336283518,1.0385701101629785,1314,0.012779819581803468,5391
-1784281326.268232,-0.0096362623873578,0.012819044946118371,0.9998713989978268,0.9312224966475169,1290,0.014104946182144612,6461
-1784281406.9641902,0.0003902542885943621,0.08032748256370953,0.9967684501661191,1.1034060039993756,1292,0.010758148594815282,7268
-1784281474.3615055,-0.03105566487178763,0.07564589746567012,0.9966510140846617,1.0327196422481995,1815,0.011041719572931458,7942
-1784281630.3553114,-0.08580403119897857,-0.004531705446499283,0.9963017273274953,0.9450482405407393,2217,0.013149265194066527,9502
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diff --git a/results/01_previous_two_batches/comparison_summary.json b/results/01_previous_two_batches/comparison_summary.json
deleted file mode 100644
index ffab318..0000000
--- a/results/01_previous_two_batches/comparison_summary.json
+++ /dev/null
@@ -1,79 +0,0 @@
-{
-  "recommended_backend": "open3d_gicp",
-  "selection_reason": "The two X estimates agree closely; Open3D has lower second-batch AX residual, better B loop closure, and lower first-batch auxiliary residual.",
-  "coordinate_convention": "T_body_lidar maps raw LiDAR points into rear-axle body frame",
-  "measured_extrinsic_used_as_initial": false,
-  "second_batch_role": "estimation (dense RTK)",
-  "first_batch_role": "auxiliary check only (sparse RTK)",
-  "backend_difference": {
-    "translation_m": 0.00181035475331947,
-    "rotation_deg": 0.06312194455789993
-  },
-  "open3d_gicp": {
-    "translation_m": [
-      1.2978831677200011,
-      -0.0030997734098957433,
-      0.7217892226151688
-    ],
-    "rotation_rpy_deg_xyz": [
-      -0.7572070226288585,
-      1.1460424368859559,
-      -0.8797812288284186
-    ],
-    "estimation_pairs": 66,
-    "estimation_translation_rms_m": 0.10017183831403174,
-    "estimation_rotation_rms_deg": 1.011529772202344,
-    "bootstrap_std": [
-      0.0020832827985508263,
-      0.002063603632322515,
-      0.001427746471392659,
-      0.07576290622767821,
-      0.06304875844333606,
-      0.07843172452171372
-    ],
-    "initial_B_loop_closure": {
-      "count": 106,
-      "translation_rms_m": 0.020350848901853437,
-      "translation_p95_m": 0.04464367942375473,
-      "rotation_rms_deg": 0.2674546762953808,
-      "rotation_p95_deg": 0.5761692075739222
-    },
-    "batch1_auxiliary_pairs": 41,
-    "batch1_auxiliary_translation_rms_m": 0.06627076507951374,
-    "batch1_auxiliary_rotation_rms_deg": 1.0783402768758907
-  },
-  "small_gicp": {
-    "translation_m": [
-      1.2996301155160686,
-      -0.0035647011612625953,
-      0.7218861757826791
-    ],
-    "rotation_rpy_deg_xyz": [
-      -0.7871563544979889,
-      1.1414557494228486,
-      -0.9357571721886107
-    ],
-    "estimation_pairs": 80,
-    "estimation_translation_rms_m": 0.11870623426762615,
-    "estimation_rotation_rms_deg": 1.135091439337232,
-    "bootstrap_std": [
-      0.0017068433472663032,
-      0.0019214288447692426,
-      0.0013180801706094514,
-      0.06849719260762097,
-      0.05792635838163369,
-      0.062093058432709465
-    ],
-    "initial_B_loop_closure": {
-      "count": 252,
-      "translation_rms_m": 0.06356464456110195,
-      "translation_p95_m": 0.12253135158224471,
-      "rotation_rms_deg": 0.7286536542725655,
-      "rotation_p95_deg": 1.4911215410143956
-    },
-    "batch1_auxiliary_pairs": 36,
-    "batch1_auxiliary_translation_rms_m": 0.07402020402512643,
-    "batch1_auxiliary_rotation_rms_deg": 1.1492603033421918
-  },
-  "important_limit": "Backend agreement is strong, but AX rotation RMS remains about one degree. This is not a centimetre-grade absolute certification."
-}
diff --git a/results/01_previous_two_batches/consensus/B_batch1_consensus.consensus.json b/results/01_previous_two_batches/consensus/B_batch1_consensus.consensus.json
deleted file mode 100644
index 87d1d02..0000000
--- a/results/01_previous_two_batches/consensus/B_batch1_consensus.consensus.json
+++ /dev/null
@@ -1,328 +0,0 @@
-{
-  "selection_is_X_independent": true,
-  "B_source": "Open3D; small_gicp is used only as an agreement gate",
-  "max_translation_m": 0.05,
-  "max_rotation_deg": 0.5,
-  "input_open3d_pairs": 41,
-  "accepted_pairs": 22,
-  "pairs": [
-    {
-      "i": 0,
-      "j": 1,
-      "open3d_small_translation_m": 0.04084575096493436,
-      "open3d_small_rotation_deg": 0.8091245488258404,
-      "accepted": false,
-      "reason": "backend_disagreement"
-    },
-    {
-      "i": 0,
-      "j": 3,
-      "open3d_small_translation_m": 0.007440836728606337,
-      "open3d_small_rotation_deg": 0.14377171116926005,
-      "accepted": true,
-      "reason": ""
-    },
-    {
-      "i": 1,
-      "j": 2,
-      "open3d_small_translation_m": 0.012040931709501762,
-      "open3d_small_rotation_deg": 0.09198739647809913,
-      "accepted": true,
-      "reason": ""
-    },
-    {
-      "i": 2,
-      "j": 3,
-      "open3d_small_translation_m": 0.020167802344555865,
-      "open3d_small_rotation_deg": 0.10088741778579047,
-      "accepted": true,
-      "reason": ""
-    },
-    {
-      "i": 2,
-      "j": 5,
-      "open3d_small_translation_m": 0.05126263142175136,
-      "open3d_small_rotation_deg": 1.129023564517054,
-      "accepted": false,
-      "reason": "backend_disagreement"
-    },
-    {
-      "i": 3,
-      "j": 4,
-      "open3d_small_translation_m": 0.008340648580577372,
-      "open3d_small_rotation_deg": 0.48893802037297335,
-      "accepted": true,
-      "reason": ""
-    },
-    {
-      "i": 3,
-      "j": 5,
-      "open3d_small_translation_m": 0.03255543023061846,
-      "open3d_small_rotation_deg": 0.04924738744939371,
-      "accepted": true,
-      "reason": ""
-    },
-    {
-      "i": 4,
-      "j": 5,
-      "open3d_small_translation_m": 0.01717130804559543,
-      "open3d_small_rotation_deg": 0.18948013657322885,
-      "accepted": true,
-      "reason": ""
-    },
-    {
-      "i": 5,
-      "j": 6,
-      "open3d_small_translation_m": 0.00790599819083906,
-      "open3d_small_rotation_deg": 0.1334214273599749,
-      "accepted": true,
-      "reason": ""
-    },
-    {
-      "i": 6,
-      "j": 7,
-      "open3d_small_translation_m": 0.02785621409489221,
-      "open3d_small_rotation_deg": 0.4203987393515618,
-      "accepted": true,
-      "reason": ""
-    },
-    {
-      "i": 6,
-      "j": 9,
-      "open3d_small_translation_m": 0.012940492880990915,
-      "open3d_small_rotation_deg": 0.16985420735800236,
-      "accepted": true,
-      "reason": ""
-    },
-    {
-      "i": 11,
-      "j": 12,
-      "open3d_small_translation_m": 0.016762449071916253,
-      "open3d_small_rotation_deg": 0.43689758943546,
-      "accepted": true,
-      "reason": ""
-    },
-    {
-      "i": 16,
-      "j": 17,
-      "open3d_small_translation_m": 0.038512603544217365,
-      "open3d_small_rotation_deg": 1.3958733432618273,
-      "accepted": false,
-      "reason": "backend_disagreement"
-    },
-    {
-      "i": 16,
-      "j": 18,
-      "accepted": false,
-      "reason": "not_in_small_gicp_refined"
-    },
-    {
-      "i": 17,
-      "j": 18,
-      "open3d_small_translation_m": 0.04386909360158492,
-      "open3d_small_rotation_deg": 0.49818041971185584,
-      "accepted": true,
-      "reason": ""
-    },
-    {
-      "i": 18,
-      "j": 19,
-      "open3d_small_translation_m": 0.02904786593904068,
-      "open3d_small_rotation_deg": 0.6456312776257432,
-      "accepted": false,
-      "reason": "backend_disagreement"
-    },
-    {
-      "i": 18,
-      "j": 20,
-      "accepted": false,
-      "reason": "not_in_small_gicp_refined"
-    },
-    {
-      "i": 18,
-      "j": 21,
-      "open3d_small_translation_m": 0.06690824468510452,
-      "open3d_small_rotation_deg": 0.5787554058174607,
-      "accepted": false,
-      "reason": "backend_disagreement"
-    },
-    {
-      "i": 19,
-      "j": 20,
-      "accepted": false,
-      "reason": "not_in_small_gicp_refined"
-    },
-    {
-      "i": 20,
-      "j": 21,
-      "open3d_small_translation_m": 0.02975935281075696,
-      "open3d_small_rotation_deg": 0.36957453812106744,
-      "accepted": true,
-      "reason": ""
-    },
-    {
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-      "accepted": true,
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-    },
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-      "open3d_small_rotation_deg": 0.14906239098917923,
-      "accepted": true,
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-    },
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-    },
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-      "open3d_small_rotation_deg": 0.19583405427516354,
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-      "accepted": true,
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-    },
-    {
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-      "open3d_small_translation_m": 0.032394639661318274,
-      "open3d_small_rotation_deg": 0.6672581993183133,
-      "accepted": false,
-      "reason": "backend_disagreement"
-    },
-    {
-      "i": 27,
-      "j": 28,
-      "open3d_small_translation_m": 0.03319908369315011,
-      "open3d_small_rotation_deg": 0.3374096789165904,
-      "accepted": true,
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-    {
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-      "accepted": false,
-      "reason": "backend_disagreement"
-    },
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-    {
-      "i": 31,
-      "j": 33,
-      "accepted": false,
-      "reason": "not_in_small_gicp_refined"
-    },
-    {
-      "i": 33,
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-      "accepted": false,
-      "reason": "not_in_small_gicp_refined"
-    },
-    {
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-      "j": 35,
-      "open3d_small_translation_m": 0.012003505646551895,
-      "open3d_small_rotation_deg": 0.2900810668840737,
-      "accepted": true,
-      "reason": ""
-    },
-    {
-      "i": 34,
-      "j": 35,
-      "open3d_small_translation_m": 0.034420937161804874,
-      "open3d_small_rotation_deg": 0.3929515224293036,
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-      "reason": ""
-    },
-    {
-      "i": 34,
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-      "open3d_small_rotation_deg": 0.5761893617071098,
-      "accepted": false,
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-      "open3d_small_rotation_deg": 0.47958651768297733,
-      "accepted": true,
-      "reason": ""
-    }
-  ]
-}
diff --git a/results/01_previous_two_batches/consensus/B_batch1_consensus.npz b/results/01_previous_two_batches/consensus/B_batch1_consensus.npz
deleted file mode 100644
index 22e8a79..0000000
Binary files a/results/01_previous_two_batches/consensus/B_batch1_consensus.npz and /dev/null differ
diff --git a/results/01_previous_two_batches/consensus/B_batch2_consensus.consensus.json b/results/01_previous_two_batches/consensus/B_batch2_consensus.consensus.json
deleted file mode 100644
index d1c5393..0000000
--- a/results/01_previous_two_batches/consensus/B_batch2_consensus.consensus.json
+++ /dev/null
@@ -1,530 +0,0 @@
-{
-  "selection_is_X_independent": true,
-  "B_source": "Open3D; small_gicp is used only as an agreement gate",
-  "max_translation_m": 0.05,
-  "max_rotation_deg": 0.5,
-  "input_open3d_pairs": 66,
-  "accepted_pairs": 39,
-  "pairs": [
-    {
-      "i": 0,
-      "j": 1,
-      "open3d_small_translation_m": 0.014112857127352833,
-      "open3d_small_rotation_deg": 0.9322795088817045,
-      "accepted": false,
-      "reason": "backend_disagreement"
-    },
-    {
-      "i": 0,
-      "j": 2,
-      "open3d_small_translation_m": 0.04048559177128157,
-      "open3d_small_rotation_deg": 0.13828514886662066,
-      "accepted": true,
-      "reason": ""
-    },
-    {
-      "i": 0,
-      "j": 3,
-      "open3d_small_translation_m": 0.043319730028129194,
-      "open3d_small_rotation_deg": 0.18606836567929377,
-      "accepted": true,
-      "reason": ""
-    },
-    {
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-      "reason": ""
-    },
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-      "open3d_small_rotation_deg": 0.3402294071905194,
-      "accepted": true,
-      "reason": ""
-    },
-    {
-      "i": 1,
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-      "accepted": false,
-      "reason": "not_in_small_gicp_refined"
-    },
-    {
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-    },
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-      "accepted": true,
-      "reason": ""
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-      "accepted": true,
-      "reason": ""
-    },
-    {
-      "i": 7,
-      "j": 10,
-      "accepted": false,
-      "reason": "not_in_small_gicp_refined"
-    },
-    {
-      "i": 8,
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-      "open3d_small_translation_m": 0.026603663511016604,
-      "open3d_small_rotation_deg": 0.3213901608387603,
-      "accepted": true,
-      "reason": ""
-    },
-    {
-      "i": 8,
-      "j": 10,
-      "open3d_small_translation_m": 0.029568992143279488,
-      "open3d_small_rotation_deg": 0.42606536158015423,
-      "accepted": true,
-      "reason": ""
-    },
-    {
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diff --git a/results/01_previous_two_batches/consensus/B_batch2_consensus.npz b/results/01_previous_two_batches/consensus/B_batch2_consensus.npz
deleted file mode 100644
index c88bcda..0000000
Binary files a/results/01_previous_two_batches/consensus/B_batch2_consensus.npz and /dev/null differ
diff --git a/results/01_previous_two_batches/consensus/batch1_auxiliary_check.json b/results/01_previous_two_batches/consensus/batch1_auxiliary_check.json
deleted file mode 100644
index 7e5874d..0000000
--- a/results/01_previous_two_batches/consensus/batch1_auxiliary_check.json
+++ /dev/null
@@ -1,179 +0,0 @@
-{
-  "role": "auxiliary check only; first-batch RTK is sparse",
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-  "note": "No AX residual was used to select these pairs",
-  "stations": 38,
-  "metrics": {
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diff --git a/results/01_previous_two_batches/consensus/extrinsic_batch2_consensus.json b/results/01_previous_two_batches/consensus/extrinsic_batch2_consensus.json
deleted file mode 100644
index 3279d38..0000000
--- a/results/01_previous_two_batches/consensus/extrinsic_batch2_consensus.json
+++ /dev/null
@@ -1,399 +0,0 @@
-{
-  "schema_version": 2,
-  "success": true,
-  "message": "`ftol` termination condition is satisfied.",
-  "convention": "T_body_lidar maps raw LiDAR points into rear-axle body frame",
-  "equation": "A_ij X = X B_ij",
-  "measured_extrinsic_used_as_initial": false,
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-    "warning": "conditional local estimate; bootstrap is the primary stability check"
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-  "bootstrap": {
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-      "pitch_deg",
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diff --git a/results/01_previous_two_batches/diagnostics/consensus_pair0_left_rpy_scan.csv b/results/01_previous_two_batches/diagnostics/consensus_pair0_left_rpy_scan.csv
deleted file mode 100644
index f8fd637..0000000
--- a/results/01_previous_two_batches/diagnostics/consensus_pair0_left_rpy_scan.csv
+++ /dev/null
@@ -1,19 +0,0 @@
-label,roll_correction_deg,pitch_correction_deg,yaw_correction_deg,selected_pair_translation_cm,selected_pair_rotation_deg,all_pair_translation_rms_m,all_pair_rotation_rms_deg,normalized_global_rms,normalized_global_rms_change,improved_pairs,worsened_pairs,global_consistency_signal,ground_normal_tilt_rms_deg,ground_height_rms_m
-baseline,0.0,0.0,0.0,13.53760421849012,0.5166365681634405,0.07984780651249465,0.961176171904301,2.4991413356769443,0.0,0,0,False,1.6662748432297785,0.03471396517121729
-pitch_+0.100,0.0,0.1,0.0,13.322368374959654,0.4851311566747633,0.07937622701088871,0.9709178397492695,2.508178616440067,0.009037280763122713,17,22,False,1.661255702204205,0.03471396517121729
-pitch_+0.200,0.0,0.2,0.0,13.107741962217032,0.45594025406310634,0.07905894857986535,0.991843015836615,2.536757223795175,0.03761588811823069,17,22,False,1.6622470214176333,0.03471396517121729
-pitch_+0.300,0.0,0.3,0.0,12.89375489636804,0.4295360884271374,0.07889765995849754,1.0232658257505307,2.5842267894606974,0.0850854537837531,16,23,False,1.669238092496052,0.034713965171217276
-pitch_+0.000_roll_-0.200,-0.2,0.0,0.0,13.395035432680281,0.501501180601739,0.08136434456273667,0.9671396098919116,2.5277457796497282,0.028604443972783944,12,27,False,1.7107124278398285,0.034713965171217304
-pitch_+0.000_roll_-0.100,-0.1,0.0,0.0,13.466127879921094,0.5071126466746416,0.08054864611850543,0.958376027630505,2.503831503507573,0.004690167830628589,13,26,False,1.685676496509504,0.034713965171217304
-pitch_+0.000_roll_+0.100,0.1,0.0,0.0,13.609457775458583,0.5298619890141043,0.07926481666577584,0.9754404878748625,2.5137822192795105,0.014640883602566213,23,16,False,1.652705907802981,0.034713965171217304
-pitch_+0.100_roll_-0.200,-0.2,0.1,0.0,13.180263465884618,0.4689801268726104,0.08100204146829142,0.9768217811391146,2.5379628557651293,0.03882152008818496,14,25,False,1.7058242505297496,0.034713965171217304
-pitch_+0.100_roll_-0.100,-0.1,0.1,0.0,13.251119920699841,0.47497594758710626,0.08013195956996022,0.9681458624297539,2.5134991588556583,0.014357823178714035,17,22,False,1.6807154082401394,0.03471396517121729
-pitch_+0.100_roll_+0.100,0.1,0.1,0.0,13.394001942784334,0.4991919434350986,0.07873808044179886,0.9850410981186302,2.5221217227950565,0.022980387118112233,19,20,False,1.6476453039285432,0.0347139651712173
-pitch_+0.200_roll_-0.200,-0.2,0.2,0.0,12.966120616418092,0.43871598020210434,0.08079188106279227,0.9976230703529106,2.567477045713792,0.0683357100368478,15,24,False,1.7067898021773054,0.034713965171217304
-pitch_+0.200_roll_-0.100,-0.1,0.2,0.0,13.036731063691272,0.44511961856905025,0.07986863254178682,0.989129669887256,2.5426579402355864,0.04351660455864215,19,20,False,1.6816953294526065,0.03471396517121731
-pitch_+0.200_roll_+0.100,0.1,0.2,0.0,13.179146202690733,0.4708734484159498,0.07836629319834118,1.0056724288764685,2.5499055866185576,0.0507642509416133,19,20,False,1.648644705864238,0.034713965171217304
-pitch_+0.300_roll_-0.200,-0.2,0.3,0.0,12.752638042306833,0.4112074527490782,0.08073488194995813,1.0288692761236073,2.6156330810711834,0.11649174539423912,15,24,False,1.7135991876939975,0.03471396517121731
-pitch_+0.300_roll_-0.100,-0.1,0.3,0.0,12.822991835578721,0.41803263983275235,0.07976001272785865,1.020636005744607,2.5906476559016074,0.0915063202246631,16,23,False,1.6886059172123598,0.0347139651712173
-pitch_+0.300_roll_+0.100,0.1,0.3,0.0,12.964919880829425,0.44535539842024163,0.07815149226179761,1.036676092226784,2.596507573236926,0.09736623755998153,18,21,False,1.6556931398905776,0.034713965171217304
-yaw_-0.200_diagnostic,0.0,0.0,-0.2,13.607478813867315,0.5166365681634414,0.08024771376258277,0.961176171904301,2.5042597228312786,0.005118387154334325,18,21,False,1.6662748432297787,0.0347139651712173
-yaw_+0.200_diagnostic,0.0,0.0,0.2,13.479715314434312,0.5166365681634427,0.08028135387591602,0.961176171904301,2.5046909681249,0.005549632447955588,13,26,False,1.6662748432297787,0.0347139651712173
diff --git a/results/01_previous_two_batches/diagnostics/consensus_pair0_left_rpy_scan.json b/results/01_previous_two_batches/diagnostics/consensus_pair0_left_rpy_scan.json
deleted file mode 100644
index 4da1000..0000000
--- a/results/01_previous_two_batches/diagnostics/consensus_pair0_left_rpy_scan.json
+++ /dev/null
@@ -1,17439 +0,0 @@
-{
-  "schema_version": 1,
-  "diagnostic_only": true,
-  "extrinsic_was_modified": false,
-  "equation": "delta_ij = B_ij^-1 * (X^-1 * A_ij * X)",
-  "correction_convention": "X_test = DeltaR_body * X; DeltaR uses fixed body xyz RPY axes",
-  "component_frame": "delta translation/RPY components are in station-j LiDAR coordinates, not screen axes",
-  "selection_rule": "Never accept a correction from selected_pair alone. Require improvement over all refined pairs, directional consistency across pairs, acceptable ground constraints, and independent visual review. This script never overwrites X.",
-  "pairs_file": "results\\01_previous_two_batches\\consensus\\B_batch2_consensus.npz",
-  "extrinsic_file": "results\\01_previous_two_batches\\final_extrinsic_recommended.json",
-  "stations": 38,
-  "pairs": 39,
-  "selected_pair_index": 0,
-  "selected_pair_stations": [
-    0,
-    2
-  ],
-  "normalization": {
-    "translation_scale_m": 0.05,
-    "rotation_scale_deg": 0.5
-  },
-  "z_observability": {
-    "body_left_z_test_shift_m": 0.1,
-    "max_predicted_motion_change_translation_m": 9.977540720306595e-16,
-    "max_predicted_motion_change_rotation_deg": 0.0,
-    "numerically_unobservable": true,
-    "note": "AX pairs cannot determine X.z when every A rotation preserves body Z; use ground/external height constraints."
-  },
-  "ranking_by_all_pair_normalized_rms": [
-    {
-      "rank": 1,
-      "label": "baseline",
-      "body_left_rpy_correction_deg_xyz": [
-        0.0,
-        0.0,
-        0.0
-      ],
-      "normalized_global_rms": 2.4991413356769443,
-      "normalized_global_rms_change": 0.0,
-      "improved_pairs": 0,
-      "worsened_pairs": 0,
-      "unchanged_pairs": 39,
-      "median_per_pair_score_change": 0.0,
-      "global_consistency_signal": false
-    },
-    {
-      "rank": 2,
-      "label": "pitch_+0.000_roll_-0.100",
-      "body_left_rpy_correction_deg_xyz": [
-        -0.1,
-        0.0,
-        0.0
-      ],
-      "normalized_global_rms": 2.503831503507573,
-      "normalized_global_rms_change": 0.004690167830628589,
-      "improved_pairs": 13,
-      "worsened_pairs": 26,
-      "unchanged_pairs": 0,
-      "median_per_pair_score_change": 0.02309094892649588,
-      "global_consistency_signal": false
-    },
-    {
-      "rank": 3,
-      "label": "yaw_-0.200_diagnostic",
-      "body_left_rpy_correction_deg_xyz": [
-        0.0,
-        0.0,
-        -0.2
-      ],
-      "normalized_global_rms": 2.5042597228312786,
-      "normalized_global_rms_change": 0.005118387154334325,
-      "improved_pairs": 18,
-      "worsened_pairs": 21,
-      "unchanged_pairs": 0,
-      "median_per_pair_score_change": 0.00023747568828058618,
-      "global_consistency_signal": false
-    },
-    {
-      "rank": 4,
-      "label": "yaw_+0.200_diagnostic",
-      "body_left_rpy_correction_deg_xyz": [
-        0.0,
-        0.0,
-        0.2
-      ],
-      "normalized_global_rms": 2.5046909681249,
-      "normalized_global_rms_change": 0.005549632447955588,
-      "improved_pairs": 13,
-      "worsened_pairs": 26,
-      "unchanged_pairs": 0,
-      "median_per_pair_score_change": 0.003543965438597585,
-      "global_consistency_signal": false
-    },
-    {
-      "rank": 5,
-      "label": "pitch_+0.100",
-      "body_left_rpy_correction_deg_xyz": [
-        0.0,
-        0.1,
-        0.0
-      ],
-      "normalized_global_rms": 2.508178616440067,
-      "normalized_global_rms_change": 0.009037280763122713,
-      "improved_pairs": 17,
-      "worsened_pairs": 22,
-      "unchanged_pairs": 0,
-      "median_per_pair_score_change": 0.004215801948034725,
-      "global_consistency_signal": false
-    },
-    {
-      "rank": 6,
-      "label": "pitch_+0.100_roll_-0.100",
-      "body_left_rpy_correction_deg_xyz": [
-        -0.1,
-        0.1,
-        0.0
-      ],
-      "normalized_global_rms": 2.5134991588556583,
-      "normalized_global_rms_change": 0.014357823178714035,
-      "improved_pairs": 17,
-      "worsened_pairs": 22,
-      "unchanged_pairs": 0,
-      "median_per_pair_score_change": 0.040343980923164935,
-      "global_consistency_signal": false
-    },
-    {
-      "rank": 7,
-      "label": "pitch_+0.000_roll_+0.100",
-      "body_left_rpy_correction_deg_xyz": [
-        0.1,
-        0.0,
-        0.0
-      ],
-      "normalized_global_rms": 2.5137822192795105,
-      "normalized_global_rms_change": 0.014640883602566213,
-      "improved_pairs": 23,
-      "worsened_pairs": 16,
-      "unchanged_pairs": 0,
-      "median_per_pair_score_change": -0.01407846496018239,
-      "global_consistency_signal": false
-    },
-    {
-      "rank": 8,
-      "label": "pitch_+0.100_roll_+0.100",
-      "body_left_rpy_correction_deg_xyz": [
-        0.1,
-        0.1,
-        0.0
-      ],
-      "normalized_global_rms": 2.5221217227950565,
-      "normalized_global_rms_change": 0.022980387118112233,
-      "improved_pairs": 19,
-      "worsened_pairs": 20,
-      "unchanged_pairs": 0,
-      "median_per_pair_score_change": 0.0017833859279048347,
-      "global_consistency_signal": false
-    },
-    {
-      "rank": 9,
-      "label": "pitch_+0.000_roll_-0.200",
-      "body_left_rpy_correction_deg_xyz": [
-        -0.2,
-        0.0,
-        0.0
-      ],
-      "normalized_global_rms": 2.5277457796497282,
-      "normalized_global_rms_change": 0.028604443972783944,
-      "improved_pairs": 12,
-      "worsened_pairs": 27,
-      "unchanged_pairs": 0,
-      "median_per_pair_score_change": 0.05528357443912335,
-      "global_consistency_signal": false
-    },
-    {
-      "rank": 10,
-      "label": "pitch_+0.200",
-      "body_left_rpy_correction_deg_xyz": [
-        0.0,
-        0.2,
-        0.0
-      ],
-      "normalized_global_rms": 2.536757223795175,
-      "normalized_global_rms_change": 0.03761588811823069,
-      "improved_pairs": 17,
-      "worsened_pairs": 22,
-      "unchanged_pairs": 0,
-      "median_per_pair_score_change": 0.02564623883043149,
-      "global_consistency_signal": false
-    },
-    {
-      "rank": 11,
-      "label": "pitch_+0.100_roll_-0.200",
-      "body_left_rpy_correction_deg_xyz": [
-        -0.2,
-        0.1,
-        0.0
-      ],
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-          "translation_norm_m": 0.022159224175349424,
-          "rotation_rpy_deg_xyz": [
-            0.8472824533054352,
-            0.6924972699468647,
-            -0.5039284014781155
-          ],
-          "rotation_angle_deg": 1.206866980510852,
-          "pair_index": 30,
-          "i": 27,
-          "j": 30
-        },
-        {
-          "translation_xyz_m": [
-            -0.0038331907039319546,
-            0.02340287336025282,
-            0.05614344570681083
-          ],
-          "translation_xyz_cm": [
-            -0.38331907039319546,
-            2.340287336025282,
-            5.614344570681083
-          ],
-          "translation_norm_m": 0.060946487415784324,
-          "rotation_rpy_deg_xyz": [
-            -1.2295910627015747,
-            -0.5146874739254865,
-            0.6115327195593013
-          ],
-          "rotation_angle_deg": 1.4642363140494412,
-          "pair_index": 31,
-          "i": 30,
-          "j": 31
-        },
-        {
-          "translation_xyz_m": [
-            0.009690735530324623,
-            0.004653170314430355,
-            0.035294328624991586
-          ],
-          "translation_xyz_cm": [
-            0.9690735530324623,
-            0.4653170314430355,
-            3.5294328624991587
-          ],
-          "translation_norm_m": 0.036895148491132165,
-          "rotation_rpy_deg_xyz": [
-            -0.31513998336533716,
-            -0.2141940157510921,
-            0.4953590423367678
-          ],
-          "rotation_angle_deg": 0.6244903967618453,
-          "pair_index": 32,
-          "i": 30,
-          "j": 32
-        },
-        {
-          "translation_xyz_m": [
-            -0.0053865347058952295,
-            -0.007425116242552987,
-            0.026573012796881706
-          ],
-          "translation_xyz_cm": [
-            -0.538653470589523,
-            -0.7425116242552987,
-            2.6573012796881708
-          ],
-          "translation_norm_m": 0.028111778962856066,
-          "rotation_rpy_deg_xyz": [
-            0.5172047347275823,
-            -1.243920438445153,
-            0.237155447967133
-          ],
-          "rotation_angle_deg": 1.3688430767407762,
-          "pair_index": 33,
-          "i": 32,
-          "j": 33
-        },
-        {
-          "translation_xyz_m": [
-            -0.020732733130354397,
-            1.4957174660823469e-05,
-            0.028656318943141107
-          ],
-          "translation_xyz_cm": [
-            -2.0732733130354397,
-            0.001495717466082347,
-            2.865631894314111
-          ],
-          "translation_norm_m": 0.03536991747435377,
-          "rotation_rpy_deg_xyz": [
-            -0.6182568414692499,
-            -1.2732199342731065,
-            0.17800383183508972
-          ],
-          "rotation_angle_deg": 1.425676324367976,
-          "pair_index": 34,
-          "i": 32,
-          "j": 34
-        },
-        {
-          "translation_xyz_m": [
-            -0.00010639052652550163,
-            0.024898921500229765,
-            -0.051552206983603015
-          ],
-          "translation_xyz_cm": [
-            -0.010639052652550163,
-            2.4898921500229765,
-            -5.155220698360301
-          ],
-          "translation_norm_m": 0.05725030703584904,
-          "rotation_rpy_deg_xyz": [
-            -0.11937661233725184,
-            -0.6309937842808361,
-            0.0919383792671678
-          ],
-          "rotation_angle_deg": 0.6486412679040614,
-          "pair_index": 35,
-          "i": 32,
-          "j": 35
-        },
-        {
-          "translation_xyz_m": [
-            -0.00486040978797142,
-            0.0002558414003355214,
-            -0.02124869507791763
-          ],
-          "translation_xyz_cm": [
-            -0.48604097879714203,
-            0.02558414003355214,
-            -2.1248695077917628
-          ],
-          "translation_norm_m": 0.021798992652034516,
-          "rotation_rpy_deg_xyz": [
-            0.11147341198359842,
-            -0.20435563963405623,
-            -0.048278644462965606
-          ],
-          "rotation_angle_deg": 0.23769553016909534,
-          "pair_index": 36,
-          "i": 33,
-          "j": 34
-        },
-        {
-          "translation_xyz_m": [
-            0.010668777398309404,
-            0.028608197246107858,
-            -0.02214058432095123
-          ],
-          "translation_xyz_cm": [
-            1.0668777398309404,
-            2.860819724610786,
-            -2.214058432095123
-          ],
-          "translation_norm_m": 0.03771547739218002,
-          "rotation_rpy_deg_xyz": [
-            1.0522317952095899,
-            0.21279800583519293,
-            -0.14258070238539514
-          ],
-          "rotation_angle_deg": 1.0832171246083169,
-          "pair_index": 37,
-          "i": 33,
-          "j": 35
-        },
-        {
-          "translation_xyz_m": [
-            0.004724714533978824,
-            0.005398902444147535,
-            0.025142779046231058
-          ],
-          "translation_xyz_cm": [
-            0.47247145339788243,
-            0.5398902444147535,
-            2.5142779046231056
-          ],
-          "translation_norm_m": 0.026146326954213064,
-          "rotation_rpy_deg_xyz": [
-            1.2132782648708806,
-            -0.1403570137683193,
-            0.021891548334274723
-          ],
-          "rotation_angle_deg": 1.2215923174512227,
-          "pair_index": 38,
-          "i": 35,
-          "j": 36
-        }
-      ],
-      "comparison_to_baseline": {
-        "normalized_global_rms_change": 0.005549632447955588,
-        "improved_pairs": 13,
-        "worsened_pairs": 26,
-        "unchanged_pairs": 0,
-        "median_per_pair_score_change": 0.003543965438597585,
-        "global_consistency_signal": false
-      }
-    }
-  ]
-}
diff --git a/results/01_previous_two_batches/diagnostics/open3d_refined_pair0_left_rpy_scan.csv b/results/01_previous_two_batches/diagnostics/open3d_refined_pair0_left_rpy_scan.csv
deleted file mode 100644
index 65c2b08..0000000
--- a/results/01_previous_two_batches/diagnostics/open3d_refined_pair0_left_rpy_scan.csv
+++ /dev/null
@@ -1,19 +0,0 @@
-label,roll_correction_deg,pitch_correction_deg,yaw_correction_deg,selected_pair_translation_cm,selected_pair_rotation_deg,all_pair_translation_rms_m,all_pair_rotation_rms_deg,normalized_global_rms,normalized_global_rms_change,improved_pairs,worsened_pairs,global_consistency_signal,ground_normal_tilt_rms_deg,ground_height_rms_m
-baseline,0.0,0.0,0.0,7.9716047501124,0.5471090190705759,0.10039155672864886,1.0152957563636194,2.855641391442648,0.0,0,0,False,1.6662748432297785,0.03471396517121729
-pitch_+0.100,0.0,0.1,0.0,7.877722926634115,0.5242415332114175,0.10031155812336309,1.0345690614552345,2.8820645462820917,0.026423154839443797,27,39,False,1.661255702204205,0.03471396517121729
-pitch_+0.200,0.0,0.2,0.0,7.783902534642328,0.5013877557627758,0.10034501725742666,1.0647782869175946,2.9262023505769332,0.07056095913428528,26,40,False,1.6622470214176333,0.03471396517121729
-pitch_+0.300,0.0,0.3,0.0,7.69014529426882,0.4785497243321324,0.1004916878666913,1.1050268752403856,2.9872678674890754,0.1316264760464274,25,41,False,1.669238092496052,0.034713965171217276
-pitch_+0.000_roll_-0.200,-0.2,0.0,0.0,7.822046878606513,0.5457706857344996,0.10257010426899679,1.0267538544989139,2.9026099336312234,0.04696854218857549,22,44,False,1.7107124278398285,0.034713965171217304
-pitch_+0.000_roll_-0.100,-0.1,0.0,0.0,7.896797905766369,0.545955313109902,0.10143505999644054,1.0151691591975842,2.870174601960012,0.014533210517364115,25,41,False,1.685676496509504,0.034713965171217304
-pitch_+0.000_roll_+0.100,0.1,0.0,0.0,8.046465471725153,0.5492256932471735,0.09944242267101946,1.0271293323765827,2.859282573021794,0.0036411815791459468,38,28,False,1.652705907802981,0.034713965171217304
-pitch_+0.100_roll_-0.200,-0.2,0.1,0.0,7.728092854641688,0.5228446714705329,0.10256719458254226,1.0458160126880083,2.929664876976855,0.07402348553420701,24,42,False,1.7058242505297496,0.034713965171217304
-pitch_+0.100_roll_-0.100,-0.1,0.1,0.0,7.802880223772661,0.5230373912267472,0.10139401948155134,1.0344448200154543,2.896999001946205,0.04135761050355713,31,35,False,1.6807154082401394,0.03471396517121729
-pitch_+0.100_roll_+0.100,0.1,0.1,0.0,7.952619015892104,0.5264501536349752,0.09932272291285332,1.0461846579706375,2.885136161262053,0.029494769819405242,30,36,False,1.6476453039285432,0.0347139651712173
-pitch_+0.200_roll_-0.200,-0.2,0.2,0.0,7.634199171873722,0.49992704876652105,0.10267526429269669,1.0757093910702569,2.9741363007059745,0.11849490926332651,27,39,False,1.7067898021773054,0.034713965171217304
-pitch_+0.200_roll_-0.100,-0.1,0.2,0.0,7.709023440769963,0.5001285987059726,0.10146524807256484,1.0646575627535269,2.9414386837539155,0.08579729231126754,30,36,False,1.6816953294526065,0.03471396517121731
-pitch_+0.200_roll_+0.100,0.1,0.2,0.0,7.8588344993060915,0.5036965847149959,0.09931755660454081,1.0760678191977628,2.928699135454269,0.07305774401162113,29,37,False,1.648644705864238,0.034713965171217304
-pitch_+0.300_roll_-0.200,-0.2,0.3,0.0,7.540367539154748,0.47701910095086286,0.102893833307342,1.1155635852142416,3.035256961724302,0.17961557028165398,25,41,False,1.7135991876939975,0.03471396517121731
-pitch_+0.300_roll_-0.100,-0.1,0.3,0.0,7.615229271779279,0.47723032409407057,0.10164837804314657,1.1049105360171487,3.0027098217989345,0.14706843035628658,25,41,False,1.6886059172123598,0.0347139651712173
-pitch_+0.300_roll_+0.100,0.1,0.3,0.0,7.7651136462045685,0.48096817789925783,0.09942680753866891,1.1159092500059349,2.989195517179804,0.13355412573715597,28,38,False,1.6556931398905776,0.034713965171217304
-yaw_-0.200_diagnostic,0.0,0.0,-0.2,7.9342751812671235,0.5471090190705757,0.10053142254152782,1.0152957563636194,2.8576089058597884,0.0019675144171404924,35,31,False,1.6662748432297787,0.0347139651712173
-yaw_+0.200_diagnostic,0.0,0.0,0.2,8.012589151848083,0.547109019070576,0.10091495789660097,1.0152957563636194,2.8630112438600364,0.007369852417388412,18,48,False,1.6662748432297787,0.0347139651712173
diff --git a/results/01_previous_two_batches/diagnostics/open3d_refined_pair0_left_rpy_scan.json b/results/01_previous_two_batches/diagnostics/open3d_refined_pair0_left_rpy_scan.json
deleted file mode 100644
index 760e8d4..0000000
--- a/results/01_previous_two_batches/diagnostics/open3d_refined_pair0_left_rpy_scan.json
+++ /dev/null
@@ -1,28131 +0,0 @@
-{
-  "schema_version": 1,
-  "diagnostic_only": true,
-  "extrinsic_was_modified": false,
-  "equation": "delta_ij = B_ij^-1 * (X^-1 * A_ij * X)",
-  "correction_convention": "X_test = DeltaR_body * X; DeltaR uses fixed body xyz RPY axes",
-  "component_frame": "delta translation/RPY components are in station-j LiDAR coordinates, not screen axes",
-  "selection_rule": "Never accept a correction from selected_pair alone. Require improvement over all refined pairs, directional consistency across pairs, acceptable ground constraints, and independent visual review. This script never overwrites X.",
-  "pairs_file": "results\\01_previous_two_batches\\open3d_gicp\\B_batch2_refined.npz",
-  "extrinsic_file": "results\\01_previous_two_batches\\final_extrinsic_recommended.json",
-  "stations": 38,
-  "pairs": 66,
-  "selected_pair_index": 0,
-  "selected_pair_stations": [
-    0,
-    1
-  ],
-  "normalization": {
-    "translation_scale_m": 0.05,
-    "rotation_scale_deg": 0.5
-  },
-  "z_observability": {
-    "body_left_z_test_shift_m": 0.1,
-    "max_predicted_motion_change_translation_m": 9.977540720306595e-16,
-    "max_predicted_motion_change_rotation_deg": 0.0,
-    "numerically_unobservable": true,
-    "note": "AX pairs cannot determine X.z when every A rotation preserves body Z; use ground/external height constraints."
-  },
-  "ranking_by_all_pair_normalized_rms": [
-    {
-      "rank": 1,
-      "label": "baseline",
-      "body_left_rpy_correction_deg_xyz": [
-        0.0,
-        0.0,
-        0.0
-      ],
-      "normalized_global_rms": 2.855641391442648,
-      "normalized_global_rms_change": 0.0,
-      "improved_pairs": 0,
-      "worsened_pairs": 0,
-      "unchanged_pairs": 66,
-      "median_per_pair_score_change": 0.0,
-      "global_consistency_signal": false
-    },
-    {
-      "rank": 2,
-      "label": "yaw_-0.200_diagnostic",
-      "body_left_rpy_correction_deg_xyz": [
-        0.0,
-        0.0,
-        -0.2
-      ],
-      "normalized_global_rms": 2.8576089058597884,
-      "normalized_global_rms_change": 0.0019675144171404924,
-      "improved_pairs": 35,
-      "worsened_pairs": 31,
-      "unchanged_pairs": 0,
-      "median_per_pair_score_change": -0.0004636456605737749,
-      "global_consistency_signal": false
-    },
-    {
-      "rank": 3,
-      "label": "pitch_+0.000_roll_+0.100",
-      "body_left_rpy_correction_deg_xyz": [
-        0.1,
-        0.0,
-        0.0
-      ],
-      "normalized_global_rms": 2.859282573021794,
-      "normalized_global_rms_change": 0.0036411815791459468,
-      "improved_pairs": 38,
-      "worsened_pairs": 28,
-      "unchanged_pairs": 0,
-      "median_per_pair_score_change": -0.014602177580218312,
-      "global_consistency_signal": false
-    },
-    {
-      "rank": 4,
-      "label": "yaw_+0.200_diagnostic",
-      "body_left_rpy_correction_deg_xyz": [
-        0.0,
-        0.0,
-        0.2
-      ],
-      "normalized_global_rms": 2.8630112438600364,
-      "normalized_global_rms_change": 0.007369852417388412,
-      "improved_pairs": 18,
-      "worsened_pairs": 48,
-      "unchanged_pairs": 0,
-      "median_per_pair_score_change": 0.00446840177433383,
-      "global_consistency_signal": false
-    },
-    {
-      "rank": 5,
-      "label": "pitch_+0.000_roll_-0.100",
-      "body_left_rpy_correction_deg_xyz": [
-        -0.1,
-        0.0,
-        0.0
-      ],
-      "normalized_global_rms": 2.870174601960012,
-      "normalized_global_rms_change": 0.014533210517364115,
-      "improved_pairs": 25,
-      "worsened_pairs": 41,
-      "unchanged_pairs": 0,
-      "median_per_pair_score_change": 0.026002343812685902,
-      "global_consistency_signal": false
-    },
-    {
-      "rank": 6,
-      "label": "pitch_+0.100",
-      "body_left_rpy_correction_deg_xyz": [
-        0.0,
-        0.1,
-        0.0
-      ],
-      "normalized_global_rms": 2.8820645462820917,
-      "normalized_global_rms_change": 0.026423154839443797,
-      "improved_pairs": 27,
-      "worsened_pairs": 39,
-      "unchanged_pairs": 0,
-      "median_per_pair_score_change": 0.009421696072265062,
-      "global_consistency_signal": false
-    },
-    {
-      "rank": 7,
-      "label": "pitch_+0.100_roll_+0.100",
-      "body_left_rpy_correction_deg_xyz": [
-        0.1,
-        0.1,
-        0.0
-      ],
-      "normalized_global_rms": 2.885136161262053,
-      "normalized_global_rms_change": 0.029494769819405242,
-      "improved_pairs": 30,
-      "worsened_pairs": 36,
-      "unchanged_pairs": 0,
-      "median_per_pair_score_change": 0.013664187192618082,
-      "global_consistency_signal": false
-    },
-    {
-      "rank": 8,
-      "label": "pitch_+0.100_roll_-0.100",
-      "body_left_rpy_correction_deg_xyz": [
-        -0.1,
-        0.1,
-        0.0
-      ],
-      "normalized_global_rms": 2.896999001946205,
-      "normalized_global_rms_change": 0.04135761050355713,
-      "improved_pairs": 31,
-      "worsened_pairs": 35,
-      "unchanged_pairs": 0,
-      "median_per_pair_score_change": 0.029706550191235692,
-      "global_consistency_signal": false
-    },
-    {
-      "rank": 9,
-      "label": "pitch_+0.000_roll_-0.200",
-      "body_left_rpy_correction_deg_xyz": [
-        -0.2,
-        0.0,
-        0.0
-      ],
-      "normalized_global_rms": 2.9026099336312234,
-      "normalized_global_rms_change": 0.04696854218857549,
-      "improved_pairs": 22,
-      "worsened_pairs": 44,
-      "unchanged_pairs": 0,
-      "median_per_pair_score_change": 0.058852162807430775,
-      "global_consistency_signal": false
-    },
-    {
-      "rank": 10,
-      "label": "pitch_+0.200",
-      "body_left_rpy_correction_deg_xyz": [
-        0.0,
-        0.2,
-        0.0
-      ],
-      "normalized_global_rms": 2.9262023505769332,
-      "normalized_global_rms_change": 0.07056095913428528,
-      "improved_pairs": 26,
-      "worsened_pairs": 40,
-      "unchanged_pairs": 0,
-      "median_per_pair_score_change": 0.032875044386196706,
-      "global_consistency_signal": false
-    },
-    {
-      "rank": 11,
-      "label": "pitch_+0.200_roll_+0.100",
-      "body_left_rpy_correction_deg_xyz": [
-        0.1,
-        0.2,
-        0.0
-      ],
-      "normalized_global_rms": 2.928699135454269,
-      "normalized_global_rms_change": 0.07305774401162113,
-      "improved_pairs": 29,
-      "worsened_pairs": 37,
-      "unchanged_pairs": 0,
-      "median_per_pair_score_change": 0.028170056427377133,
-      "global_consistency_signal": false
-    },
-    {
-      "rank": 12,
-      "label": "pitch_+0.100_roll_-0.200",
-      "body_left_rpy_correction_deg_xyz": [
-        -0.2,
-        0.1,
-        0.0
-      ],
-      "normalized_global_rms": 2.929664876976855,
-      "normalized_global_rms_change": 0.07402348553420701,
-      "improved_pairs": 24,
-      "worsened_pairs": 42,
-      "unchanged_pairs": 0,
-      "median_per_pair_score_change": 0.08265109992793152,
-      "global_consistency_signal": false
-    },
-    {
-      "rank": 13,
-      "label": "pitch_+0.200_roll_-0.100",
-      "body_left_rpy_correction_deg_xyz": [
-        -0.1,
-        0.2,
-        0.0
-      ],
-      "normalized_global_rms": 2.9414386837539155,
-      "normalized_global_rms_change": 0.08579729231126754,
-      "improved_pairs": 30,
-      "worsened_pairs": 36,
-      "unchanged_pairs": 0,
-      "median_per_pair_score_change": 0.04173782588453678,
-      "global_consistency_signal": false
-    },
-    {
-      "rank": 14,
-      "label": "pitch_+0.200_roll_-0.200",
-      "body_left_rpy_correction_deg_xyz": [
-        -0.2,
-        0.2,
-        0.0
-      ],
-      "normalized_global_rms": 2.9741363007059745,
-      "normalized_global_rms_change": 0.11849490926332651,
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diff --git a/results/01_previous_two_batches/diagnostics/small_gicp_refined_pair0_left_rpy_scan.csv b/results/01_previous_two_batches/diagnostics/small_gicp_refined_pair0_left_rpy_scan.csv
deleted file mode 100644
index f3dcbce..0000000
--- a/results/01_previous_two_batches/diagnostics/small_gicp_refined_pair0_left_rpy_scan.csv
+++ /dev/null
@@ -1,19 +0,0 @@
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-pitch_+0.300_roll_+0.100,0.1,0.3,0.0,8.96562003954328,0.45998721539756443,0.11828455597352863,1.2562925755921872,3.4510257337050003,0.1547901164802652,29,51,False,1.6556931398905776,0.034713965171217304
-yaw_-0.200_diagnostic,0.0,0.0,-0.2,9.118174501598277,0.39481317928354154,0.11873527555886121,1.142526017283429,3.295555956965929,-0.0006796602588061695,45,35,True,1.6662748432297787,0.0347139651712173
-yaw_+0.200_diagnostic,0.0,0.0,0.2,9.225647367504836,0.39481317928354204,0.1194719055604376,1.142526017283429,3.306187727273662,0.009952110048927043,27,53,False,1.6662748432297787,0.0347139651712173
diff --git a/results/01_previous_two_batches/diagnostics/small_gicp_refined_pair0_left_rpy_scan.json b/results/01_previous_two_batches/diagnostics/small_gicp_refined_pair0_left_rpy_scan.json
deleted file mode 100644
index ad9225b..0000000
--- a/results/01_previous_two_batches/diagnostics/small_gicp_refined_pair0_left_rpy_scan.json
+++ /dev/null
@@ -1,33675 +0,0 @@
-{
-  "schema_version": 1,
-  "diagnostic_only": true,
-  "extrinsic_was_modified": false,
-  "equation": "delta_ij = B_ij^-1 * (X^-1 * A_ij * X)",
-  "correction_convention": "X_test = DeltaR_body * X; DeltaR uses fixed body xyz RPY axes",
-  "component_frame": "delta translation/RPY components are in station-j LiDAR coordinates, not screen axes",
-  "selection_rule": "Never accept a correction from selected_pair alone. Require improvement over all refined pairs, directional consistency across pairs, acceptable ground constraints, and independent visual review. This script never overwrites X.",
-  "pairs_file": "results\\01_previous_two_batches\\small_gicp\\B_batch2_refined.npz",
-  "extrinsic_file": "results\\01_previous_two_batches\\final_extrinsic_recommended.json",
-  "stations": 38,
-  "pairs": 80,
-  "selected_pair_index": 0,
-  "selected_pair_stations": [
-    0,
-    1
-  ],
-  "normalization": {
-    "translation_scale_m": 0.05,
-    "rotation_scale_deg": 0.5
-  },
-  "z_observability": {
-    "body_left_z_test_shift_m": 0.1,
-    "max_predicted_motion_change_translation_m": 9.977540720306595e-16,
-    "max_predicted_motion_change_rotation_deg": 0.0,
-    "numerically_unobservable": true,
-    "note": "AX pairs cannot determine X.z when every A rotation preserves body Z; use ground/external height constraints."
-  },
-  "ranking_by_all_pair_normalized_rms": [
-    {
-      "rank": 1,
-      "label": "yaw_-0.200_diagnostic",
-      "body_left_rpy_correction_deg_xyz": [
-        0.0,
-        0.0,
-        -0.2
-      ],
-      "normalized_global_rms": 3.295555956965929,
-      "normalized_global_rms_change": -0.0006796602588061695,
-      "improved_pairs": 45,
-      "worsened_pairs": 35,
-      "unchanged_pairs": 0,
-      "median_per_pair_score_change": -0.0021608242414224432,
-      "global_consistency_signal": true
-    },
-    {
-      "rank": 2,
-      "label": "baseline",
-      "body_left_rpy_correction_deg_xyz": [
-        0.0,
-        0.0,
-        0.0
-      ],
-      "normalized_global_rms": 3.296235617224735,
-      "normalized_global_rms_change": 0.0,
-      "improved_pairs": 0,
-      "worsened_pairs": 0,
-      "unchanged_pairs": 80,
-      "median_per_pair_score_change": 0.0,
-      "global_consistency_signal": false
-    },
-    {
-      "rank": 3,
-      "label": "pitch_+0.000_roll_+0.100",
-      "body_left_rpy_correction_deg_xyz": [
-        0.1,
-        0.0,
-        0.0
-      ],
-      "normalized_global_rms": 3.3010571825949637,
-      "normalized_global_rms_change": 0.004821565370228598,
-      "improved_pairs": 39,
-      "worsened_pairs": 41,
-      "unchanged_pairs": 0,
-      "median_per_pair_score_change": 0.0017696484744595953,
-      "global_consistency_signal": false
-    },
-    {
-      "rank": 4,
-      "label": "yaw_+0.200_diagnostic",
-      "body_left_rpy_correction_deg_xyz": [
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-        0.2
-      ],
-      "normalized_global_rms": 3.306187727273662,
-      "normalized_global_rms_change": 0.009952110048927043,
-      "improved_pairs": 27,
-      "worsened_pairs": 53,
-      "unchanged_pairs": 0,
-      "median_per_pair_score_change": 0.005036973923611132,
-      "global_consistency_signal": false
-    },
-    {
-      "rank": 5,
-      "label": "pitch_+0.000_roll_-0.100",
-      "body_left_rpy_correction_deg_xyz": [
-        -0.1,
-        0.0,
-        0.0
-      ],
-      "normalized_global_rms": 3.3112438616237037,
-      "normalized_global_rms_change": 0.015008244398968529,
-      "improved_pairs": 36,
-      "worsened_pairs": 44,
-      "unchanged_pairs": 0,
-      "median_per_pair_score_change": 0.022882341914364612,
-      "global_consistency_signal": false
-    },
-    {
-      "rank": 6,
-      "label": "pitch_+0.100",
-      "body_left_rpy_correction_deg_xyz": [
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-        0.0
-      ],
-      "normalized_global_rms": 3.3274291807303316,
-      "normalized_global_rms_change": 0.031193563505596433,
-      "improved_pairs": 37,
-      "worsened_pairs": 43,
-      "unchanged_pairs": 0,
-      "median_per_pair_score_change": 0.027643515853556178,
-      "global_consistency_signal": false
-    },
-    {
-      "rank": 7,
-      "label": "pitch_+0.100_roll_+0.100",
-      "body_left_rpy_correction_deg_xyz": [
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-        0.1,
-        0.0
-      ],
-      "normalized_global_rms": 3.331793234208173,
-      "normalized_global_rms_change": 0.035557616983437956,
-      "improved_pairs": 33,
-      "worsened_pairs": 47,
-      "unchanged_pairs": 0,
-      "median_per_pair_score_change": 0.021922643950929743,
-      "global_consistency_signal": false
-    },
-    {
-      "rank": 8,
-      "label": "pitch_+0.100_roll_-0.100",
-      "body_left_rpy_correction_deg_xyz": [
-        -0.1,
-        0.1,
-        0.0
-      ],
-      "normalized_global_rms": 3.342708269995132,
-      "normalized_global_rms_change": 0.046472652770396916,
-      "improved_pairs": 34,
-      "worsened_pairs": 46,
-      "unchanged_pairs": 0,
-      "median_per_pair_score_change": 0.03779273410144712,
-      "global_consistency_signal": false
-    },
-    {
-      "rank": 9,
-      "label": "pitch_+0.000_roll_-0.200",
-      "body_left_rpy_correction_deg_xyz": [
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-      ],
-      "normalized_global_rms": 3.3458153318563415,
-      "normalized_global_rms_change": 0.049579714631606375,
-      "improved_pairs": 32,
-      "worsened_pairs": 48,
-      "unchanged_pairs": 0,
-      "median_per_pair_score_change": 0.04862337050743348,
-      "global_consistency_signal": false
-    },
-    {
-      "rank": 10,
-      "label": "pitch_+0.100_roll_-0.200",
-      "body_left_rpy_correction_deg_xyz": [
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-      ],
-      "normalized_global_rms": 3.3773641697603143,
-      "normalized_global_rms_change": 0.08112855253557916,
-      "improved_pairs": 35,
-      "worsened_pairs": 45,
-      "unchanged_pairs": 0,
-      "median_per_pair_score_change": 0.07613696756808985,
-      "global_consistency_signal": false
-    },
-    {
-      "rank": 11,
-      "label": "pitch_+0.200",
-      "body_left_rpy_correction_deg_xyz": [
-        0.0,
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-        0.0
-      ],
-      "normalized_global_rms": 3.378175724075376,
-      "normalized_global_rms_change": 0.08194010685064068,
-      "improved_pairs": 33,
-      "worsened_pairs": 47,
-      "unchanged_pairs": 0,
-      "median_per_pair_score_change": 0.0682090297399528,
-      "global_consistency_signal": false
-    },
-    {
-      "rank": 12,
-      "label": "pitch_+0.200_roll_+0.100",
-      "body_left_rpy_correction_deg_xyz": [
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-        0.2,
-        0.0
-      ],
-      "normalized_global_rms": 3.3820679918494174,
-      "normalized_global_rms_change": 0.0858323746246823,
-      "improved_pairs": 32,
-      "worsened_pairs": 48,
-      "unchanged_pairs": 0,
-      "median_per_pair_score_change": 0.07205204282391175,
-      "global_consistency_signal": false
-    },
-    {
-      "rank": 13,
-      "label": "pitch_+0.200_roll_-0.100",
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diff --git a/results/01_previous_two_batches/final_extrinsic_deployment.json b/results/01_previous_two_batches/final_extrinsic_deployment.json
deleted file mode 100644
index 43f7022..0000000
--- a/results/01_previous_two_batches/final_extrinsic_deployment.json
+++ /dev/null
@@ -1,46 +0,0 @@
-{
-    "convention":  "T_body_lidar maps raw LiDAR points into rear-axle body frame",
-    "translation_m":  [
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-                          -0.00006733076264476427,
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diff --git a/results/01_previous_two_batches/final_extrinsic_recommended.json b/results/01_previous_two_batches/final_extrinsic_recommended.json
deleted file mode 100644
index bdfe44e..0000000
--- a/results/01_previous_two_batches/final_extrinsic_recommended.json
+++ /dev/null
@@ -1,405 +0,0 @@
-{
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-      -0.005413227092587022,
-      0.7171569502776788,
-      -0.9695959273616203,
-      1.066246526462818,
-      -1.100751980508544
-    ],
-    "p975": [
-      1.3034038047298853,
-      0.007138524793626496,
-      0.7235834879340349,
-      -0.6076030002143074,
-      1.3517461178267727,
-      -0.6468477685453492
-    ]
-  },
-  "selection": {
-    "method": "Open3D B gated by Open3D-small_gicp cross-backend agreement",
-    "selection_is_X_independent": true,
-    "consensus_pair_threshold": "Open3D-small_gicp B delta <= 0.05 m and <= 0.50 deg",
-    "warning": "AX rotation RMS remains about one degree; this is not centimetre-grade absolute certification."
-  }
-}
diff --git a/results/01_previous_two_batches/final_summary.json b/results/01_previous_two_batches/final_summary.json
deleted file mode 100644
index 191ee6a..0000000
--- a/results/01_previous_two_batches/final_summary.json
+++ /dev/null
@@ -1,440 +0,0 @@
-{
-  "recommended_method": "Open3D B gated by Open3D-small_gicp cross-backend agreement",
-  "selection_is_X_independent": true,
-  "second_batch_role": "estimation (dense RTK)",
-  "first_batch_role": "auxiliary check only (sparse RTK)",
-  "consensus": {
-    "translation_m": [
-      1.2977596922478565,
-      -6.733076264476427e-05,
-      0.7204978345266887
-    ],
-    "rotation_rpy_deg_xyz": [
-      -0.7851511464150316,
-      1.2026608220810453,
-      -0.835510052785851
-    ],
-    "estimation": {
-      "pairs": 39,
-      "translation_m": {
-        "rms": 0.07984780651249465,
-        "median": 0.05392926910429046,
-        "p90": 0.11822807898946641,
-        "p95": 0.14420733112402187,
-        "max": 0.2330103519747209
-      },
-      "rotation_deg": {
-        "rms": 0.961176171904301,
-        "median": 0.8002960897011372,
-        "p90": 1.422624767604584,
-        "p95": 1.4793113785217964,
-        "max": 1.7237415928660533
-      },
-      "per_pair": [
-        {
-          "pair_index": 0,
-          "translation_m": 0.1353760421849012,
-          "rotation_deg": 0.5166365681634405
-        },
-        {
-          "pair_index": 1,
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-          "rotation_deg": 0.5717221816616095
-        },
-        {
-          "pair_index": 2,
-          "translation_m": 0.06210064976174764,
-          "rotation_deg": 0.4402983357286552
-        },
-        {
-          "pair_index": 3,
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-          "rotation_deg": 0.5821611725015269
-        },
-        {
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-          "rotation_deg": 0.32738975448002894
-        },
-        {
-          "pair_index": 5,
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-        {
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-        },
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-          "pair_index": 7,
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-        {
-          "pair_index": 9,
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-          "pair_index": 10,
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-        {
-          "pair_index": 11,
-          "translation_m": 0.06488404028756532,
-          "rotation_deg": 0.05192051717362457
-        },
-        {
-          "pair_index": 12,
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-          "rotation_deg": 0.9937108406424444
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-        {
-          "pair_index": 13,
-          "translation_m": 0.05392926910429046,
-          "rotation_deg": 0.9700546737541248
-        },
-        {
-          "pair_index": 14,
-          "translation_m": 0.02302185790244543,
-          "rotation_deg": 1.6149869587730064
-        },
-        {
-          "pair_index": 15,
-          "translation_m": 0.2330103519747209,
-          "rotation_deg": 0.5939965715201481
-        },
-        {
-          "pair_index": 16,
-          "translation_m": 0.2236889315761065,
-          "rotation_deg": 1.1151964340680336
-        },
-        {
-          "pair_index": 17,
-          "translation_m": 0.04090994021171706,
-          "rotation_deg": 0.7785618518380144
-        },
-        {
-          "pair_index": 18,
-          "translation_m": 0.054652520003134704,
-          "rotation_deg": 1.124375763416717
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-        {
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-        {
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-        {
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-          "rotation_deg": 1.124691549503354
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-          "rotation_deg": 1.1184574012171749
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-        {
-          "pair_index": 24,
-          "translation_m": 0.06305629062353875,
-          "rotation_deg": 0.5252019728243343
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-        {
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-          "rotation_deg": 1.3688430767407767
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-        {
-          "pair_index": 34,
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-          "rotation_deg": 1.4256763243679755
-        },
-        {
-          "pair_index": 35,
-          "translation_m": 0.054240160043693975,
-          "rotation_deg": 0.6486412679040612
-        },
-        {
-          "pair_index": 36,
-          "translation_m": 0.021992835671895014,
-          "rotation_deg": 0.23769553016909395
-        },
-        {
-          "pair_index": 37,
-          "translation_m": 0.031890552923517286,
-          "rotation_deg": 1.0832171246083164
-        },
-        {
-          "pair_index": 38,
-          "translation_m": 0.025286131886091672,
-          "rotation_deg": 1.2215923174512224
-        }
-      ]
-    },
-    "bootstrap_std": [
-      0.003223574650236103,
-      0.003334649335095665,
-      0.0016858977028131694,
-      0.0980155224808408,
-      0.07461769310738842,
-      0.11886090357304822
-    ],
-    "batch1_auxiliary": {
-      "pairs": 22,
-      "translation_m": {
-        "rms": 0.06067269746244947,
-        "median": 0.042680679229823305,
-        "p90": 0.090942947259565,
-        "p95": 0.10135707648063859,
-        "max": 0.14643003383767556
-      },
-      "rotation_deg": {
-        "rms": 1.002984942285067,
-        "median": 0.707406938077333,
-        "p90": 1.573355332434981,
-        "p95": 1.7757584051966382,
-        "max": 1.8710372365314285
-      },
-      "per_pair": [
-        {
-          "pair_index": 0,
-          "translation_m": 0.048343805321803004,
-          "rotation_deg": 0.6668376546913104,
-          "i": 0,
-          "j": 3
-        },
-        {
-          "pair_index": 1,
-          "translation_m": 0.0423483041362295,
-          "rotation_deg": 1.7859688557628564,
-          "i": 1,
-          "j": 2
-        },
-        {
-          "pair_index": 2,
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-          "rotation_deg": 1.8710372365314285,
-          "i": 2,
-          "j": 3
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-        {
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-          "j": 4
-        },
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-          "pair_index": 4,
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-          "pair_index": 7,
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-          "i": 6,
-          "j": 7
-        },
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-          "i": 6,
-          "j": 9
-        },
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-          "i": 20,
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-        },
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-          "rotation_deg": 0.7096084761069892,
-          "i": 20,
-          "j": 23
-        },
-        {
-          "pair_index": 14,
-          "translation_m": 0.07267248449673575,
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-          "i": 21,
-          "j": 24
-        },
-        {
-          "pair_index": 15,
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-          "rotation_deg": 0.537164719319421,
-          "i": 22,
-          "j": 23
-        },
-        {
-          "pair_index": 16,
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-          "i": 22,
-          "j": 24
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-        {
-          "pair_index": 17,
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-          "i": 24,
-          "j": 26
-        },
-        {
-          "pair_index": 18,
-          "translation_m": 0.0344886352240195,
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-          "i": 27,
-          "j": 28
-        },
-        {
-          "pair_index": 19,
-          "translation_m": 0.14643003383767556,
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-          "i": 33,
-          "j": 35
-        },
-        {
-          "pair_index": 20,
-          "translation_m": 0.08545677470499786,
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-          "i": 34,
-          "j": 35
-        },
-        {
-          "pair_index": 21,
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-          "rotation_deg": 1.5817598444384953,
-          "i": 35,
-          "j": 36
-        }
-      ]
-    }
-  },
-  "separate_backend_results": {
-    "open3d_gicp": {
-      "translation_m": [
-        1.2978831677200011,
-        -0.0030997734098957433,
-        0.7217892226151688
-      ],
-      "rotation_rpy_deg_xyz": [
-        -0.7572070226288585,
-        1.1460424368859559,
-        -0.8797812288284186
-      ]
-    },
-    "small_gicp": {
-      "translation_m": [
-        1.2996301155160686,
-        -0.0035647011612625953,
-        0.7218861757826791
-      ],
-      "rotation_rpy_deg_xyz": [
-        -0.7871563544979889,
-        1.1414557494228486,
-        -0.9357571721886107
-      ]
-    }
-  },
-  "warning": "AX rotation RMS remains about one degree; this is not centimetre-grade absolute certification."
-}
diff --git a/results/01_previous_two_batches/open3d_gicp/B_batch1_auxiliary.npz b/results/01_previous_two_batches/open3d_gicp/B_batch1_auxiliary.npz
deleted file mode 100644
index 989f148..0000000
Binary files a/results/01_previous_two_batches/open3d_gicp/B_batch1_auxiliary.npz and /dev/null differ
diff --git a/results/01_previous_two_batches/open3d_gicp/B_batch1_auxiliary_refined.npz b/results/01_previous_two_batches/open3d_gicp/B_batch1_auxiliary_refined.npz
deleted file mode 100644
index bff93f7..0000000
Binary files a/results/01_previous_two_batches/open3d_gicp/B_batch1_auxiliary_refined.npz and /dev/null differ
diff --git a/results/01_previous_two_batches/open3d_gicp/B_batch1_auxiliary_refined.refinement.json b/results/01_previous_two_batches/open3d_gicp/B_batch1_auxiliary_refined.refinement.json
deleted file mode 100644
index e66c870..0000000
--- a/results/01_previous_two_batches/open3d_gicp/B_batch1_auxiliary_refined.refinement.json
+++ /dev/null
@@ -1,1267 +0,0 @@
-{
-  "selection_is_X_independent": true,
-  "criteria": {
-    "min_inlier_ratio": 0.7,
-    "max_inlier_rmse_m": 0.13,
-    "max_rotation_invariant_error_deg": 0.75,
-    "reverse_translation_tolerance_m": 0.05,
-    "reverse_rotation_tolerance_deg": 0.5
-  },
-  "input_pairs": 101,
-  "accepted_pairs": 41,
-  "pairs": [
-    {
-      "i": 0,
-      "j": 1,
-      "heldout_inlier_ratio": 0.742135248947238,
-      "heldout_inlier_rmse_m": 0.1176855237061111,
-      "rotation_invariant_error_deg": 0.21067513987843967,
-      "reverse_translation_m": 0.013825313356667012,
-      "reverse_rotation_deg": 0.06962701621921227,
-      "accepted": true,
-      "rejection_reasons": []
-    },
-    {
-      "i": 0,
-      "j": 2,
-      "heldout_inlier_ratio": 0.6152139070398225,
-      "heldout_inlier_rmse_m": 0.12748244203393638,
-      "rotation_invariant_error_deg": 0.06831265614486703,
-      "reverse_translation_m": 0.010848197501521375,
-      "reverse_rotation_deg": 0.23936253539883626,
-      "accepted": false,
-      "rejection_reasons": [
-        "overlap_ratio"
-      ]
-    },
-    {
-      "i": 0,
-      "j": 3,
-      "heldout_inlier_ratio": 0.7200942109830172,
-      "heldout_inlier_rmse_m": 0.11742249635115339,
-      "rotation_invariant_error_deg": 0.6202544008851092,
-      "reverse_translation_m": 0.010896220625647894,
-      "reverse_rotation_deg": 0.1047126090415015,
-      "accepted": true,
-      "rejection_reasons": []
-    },
-    {
-      "i": 1,
-      "j": 2,
-      "heldout_inlier_ratio": 0.7419273778112828,
-      "heldout_inlier_rmse_m": 0.11333156226718596,
-      "rotation_invariant_error_deg": 0.5215102537074472,
-      "reverse_translation_m": 0.011700301190659394,
-      "reverse_rotation_deg": 0.07531112640817904,
-      "accepted": true,
-      "rejection_reasons": []
-    },
-    {
-      "i": 1,
-      "j": 3,
-      "heldout_inlier_ratio": 0.860897030953885,
-      "heldout_inlier_rmse_m": 0.10772639754828932,
-      "rotation_invariant_error_deg": 0.8383915112404274,
-      "reverse_translation_m": 0.0031419813068167823,
-      "reverse_rotation_deg": 0.07553165598013784,
-      "accepted": false,
-      "rejection_reasons": [
-        "rotation_conjugacy_invariant"
-      ]
-    },
-    {
-      "i": 1,
-      "j": 4,
-      "heldout_inlier_ratio": 0.881875,
-      "heldout_inlier_rmse_m": 0.10577894988132426,
-      "rotation_invariant_error_deg": 1.4124868370453285,
-      "reverse_translation_m": 0.004385743087150129,
-      "reverse_rotation_deg": 0.11984963227966941,
-      "accepted": false,
-      "rejection_reasons": [
-        "rotation_conjugacy_invariant"
-      ]
-    },
-    {
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-      "rotation_invariant_error_deg": 0.37708448280603335,
-      "reverse_translation_m": 0.008219359847113026,
-      "reverse_rotation_deg": 0.1277049389798412,
-      "accepted": true,
-      "rejection_reasons": []
-    },
-    {
-      "i": 2,
-      "j": 4,
-      "heldout_inlier_ratio": 0.7129525942515864,
-      "heldout_inlier_rmse_m": 0.11823277244188567,
-      "rotation_invariant_error_deg": 1.0083488113435806,
-      "reverse_translation_m": 0.003926646926802803,
-      "reverse_rotation_deg": 0.12676782091003777,
-      "accepted": false,
-      "rejection_reasons": [
-        "rotation_conjugacy_invariant"
-      ]
-    },
-    {
-      "i": 2,
-      "j": 5,
-      "heldout_inlier_ratio": 0.7434186132740082,
-      "heldout_inlier_rmse_m": 0.11591916677323456,
-      "rotation_invariant_error_deg": 0.3837872805370992,
-      "reverse_translation_m": 0.005762289421636631,
-      "reverse_rotation_deg": 0.0417195018069042,
-      "accepted": true,
-      "rejection_reasons": []
-    },
-    {
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-      "heldout_inlier_rmse_m": 0.11198421236679276,
-      "rotation_invariant_error_deg": 0.5743898299625982,
-      "reverse_translation_m": 0.016040499501420776,
-      "reverse_rotation_deg": 0.10475252258183747,
-      "accepted": true,
-      "rejection_reasons": []
-    },
-    {
-      "i": 3,
-      "j": 5,
-      "heldout_inlier_ratio": 0.7942090219957748,
-      "heldout_inlier_rmse_m": 0.1150960059583273,
-      "rotation_invariant_error_deg": 0.08998045051255588,
-      "reverse_translation_m": 0.01716401750472473,
-      "reverse_rotation_deg": 0.19985666972488197,
-      "accepted": true,
-      "rejection_reasons": []
-    },
-    {
-      "i": 3,
-      "j": 6,
-      "heldout_inlier_ratio": 0.6534504391468005,
-      "heldout_inlier_rmse_m": 0.12221285442048085,
-      "rotation_invariant_error_deg": 0.29362645810122956,
-      "reverse_translation_m": 0.010758157432153631,
-      "reverse_rotation_deg": 0.2541461196933768,
-      "accepted": false,
-      "rejection_reasons": [
-        "overlap_ratio"
-      ]
-    },
-    {
-      "i": 4,
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diff --git a/results/01_previous_two_batches/open3d_gicp/B_batch1_quality.csv b/results/01_previous_two_batches/open3d_gicp/B_batch1_quality.csv
deleted file mode 100644
index feb7573..0000000
--- a/results/01_previous_two_batches/open3d_gicp/B_batch1_quality.csv
+++ /dev/null
@@ -1,109 +0,0 @@
-i,j,rtk_translation_m,rtk_rotation_deg,heldout_inlier_ratio,heldout_inlier_rmse_m,hessian_rank,hessian_condition,reverse_translation_m,reverse_rotation_deg,multistart_success_rate,accepted,rejection_reasons
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diff --git a/results/01_previous_two_batches/open3d_gicp/B_batch1_quality.json b/results/01_previous_two_batches/open3d_gicp/B_batch1_quality.json
deleted file mode 100644
index 9658f02..0000000
--- a/results/01_previous_two_batches/open3d_gicp/B_batch1_quality.json
+++ /dev/null
@@ -1,13475 +0,0 @@
-{
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-    "frames": "C:\\Users\\admin\\Documents\\Codex\\2026-07-15\\wo\\outputs\\calibration_20260717\\prepared\\frames_all",
-    "body": "C:\\Users\\admin\\Documents\\Codex\\2026-07-15\\wo\\outputs\\calibration_20260717\\prepared\\body_poses_rear_gga_raw_rear_to_front.csv",
-    "output": "C:\\Users\\admin\\Documents\\Codex\\2026-07-15\\wo\\rigorous_build\\results\\open3d_gicp\\B_batch1_auxiliary.npz",
-    "quality_json": "C:\\Users\\admin\\Documents\\Codex\\2026-07-15\\wo\\rigorous_build\\results\\open3d_gicp\\B_batch1_quality.json",
-    "quality_csv": "C:\\Users\\admin\\Documents\\Codex\\2026-07-15\\wo\\rigorous_build\\results\\open3d_gicp\\B_batch1_quality.csv",
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diff --git a/results/01_previous_two_batches/open3d_gicp/B_batch2_estimation.npz b/results/01_previous_two_batches/open3d_gicp/B_batch2_estimation.npz
deleted file mode 100644
index 80607ec..0000000
Binary files a/results/01_previous_two_batches/open3d_gicp/B_batch2_estimation.npz and /dev/null differ
diff --git a/results/01_previous_two_batches/open3d_gicp/B_batch2_quality.csv b/results/01_previous_two_batches/open3d_gicp/B_batch2_quality.csv
deleted file mode 100644
index 85953ae..0000000
--- a/results/01_previous_two_batches/open3d_gicp/B_batch2_quality.csv
+++ /dev/null
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diff --git a/results/01_previous_two_batches/open3d_gicp/B_batch2_quality.json b/results/01_previous_two_batches/open3d_gicp/B_batch2_quality.json
deleted file mode 100644
index 6737012..0000000
--- a/results/01_previous_two_batches/open3d_gicp/B_batch2_quality.json
+++ /dev/null
@@ -1,13458 +0,0 @@
-{
-  "schema_version": 2,
-  "backend": "open3d",
-  "transform_convention": "B_ij=T_Li_Lj maps station j points into station i",
-  "raw_point_field": "points_raw",
-  "measured_extrinsic_used_as_initial": false,
-  "stations": 38,
-  "candidate_pairs": 108,
-  "accepted_pairs": 108,
-  "parameters": {
-    "command": "pairs",
-    "backend": "open3d",
-    "frames": "C:\\Users\\admin\\Documents\\Codex\\2026-07-15\\wo\\outputs\\calibration_data1_20260720\\prepared\\frames_all",
-    "body": "C:\\Users\\admin\\Documents\\Codex\\2026-07-15\\wo\\outputs\\calibration_data1_20260720\\prepared\\body_poses_rear_gga_raw_rear_to_front.csv",
-    "output": "C:\\Users\\admin\\Documents\\Codex\\2026-07-15\\wo\\rigorous_build\\results\\open3d_gicp\\B_batch2_estimation.npz",
-    "quality_json": "C:\\Users\\admin\\Documents\\Codex\\2026-07-15\\wo\\rigorous_build\\results\\open3d_gicp\\B_batch2_quality.json",
-    "quality_csv": "C:\\Users\\admin\\Documents\\Codex\\2026-07-15\\wo\\rigorous_build\\results\\open3d_gicp\\B_batch2_quality.csv",
-    "time_offset": 0.0,
-    "min_stations": 30,
-    "min_pairs": 25,
-    "min_gap": 1,
-    "max_gap": 3,
-    "min_translation": 0.5,
-    "min_rotation": 3.0,
-    "min_range": 2.0,
-    "max_range": 50.0,
-    "z_min": -0.6,
-    "z_max": 5.0,
-    "min_roi_points": 1000,
-    "holdout_fraction": 0.2,
-    "voxels": [
-      0.3,
-      0.15,
-      0.08
-    ],
-    "correspondences": [
-      1.2,
-      0.5,
-      0.25
-    ],
-    "iterations": 40,
-    "threads": 8,
-    "evaluation_distance": 0.25,
-    "min_inlier_ratio": 0.35,
-    "max_inlier_rmse": 0.16,
-    "max_hessian_condition": 100000000.0,
-    "reverse_translation_tolerance": 0.08,
-    "reverse_rotation_tolerance": 0.5,
-    "multistart": 1,
-    "multistart_translation_sigma": 0.3,
-    "multistart_rotation_sigma": 3.0,
-    "multistart_translation_tolerance": 0.08,
-    "multistart_rotation_tolerance": 0.5,
-    "min_multistart_success": 0.5,
-    "seed": 20260721
-  },
-  "accepted_loop_closure": {
-    "count": 106,
-    "translation_rms_m": 0.020350848901853437,
-    "translation_p95_m": 0.04464367942375473,
-    "rotation_rms_deg": 0.2674546762953808,
-    "rotation_p95_deg": 0.5761692075739222
-  },
-  "pairs": [
-    {
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-      "j": 1,
-      "lidar_time_i": 1784279335.9505181,
-      "lidar_time_j": 1784279429.4466305,
-      "frame_counter_i": 190,
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-      "rtk_rotation_deg": 13.198324485965863,
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-      "nearest_rtk_dt_j_s": 0.0,
-      "initial_B_source": "X0=identity; B0=A (no measured extrinsic)",
-      "B_ij_4x4": [
-        [
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-          0.22869150395714602,
-          0.002297643417305223,
-          -0.5126455200449422
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-        [
-          -0.22863457813529,
-          0.9734014906396613,
-          -0.014689033371339515,
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-          -0.015177554516289335
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-        [
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-        ]
-      ],
-      "backend": "open3d",
-      "backend_converged": null,
-      "backend_iterations": null,
-      "backend_num_inliers": 8280,
-      "backend_objective": 96.77878203533326,
-      "backend_elapsed_sec": 0.47972870000376133,
-      "multiscale_stages": [
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-          "target_points": 4045,
-          "source_points": 3930
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-          "source_points": 7415
-        },
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-          "source_points": 10961
-        }
-      ],
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diff --git a/results/01_previous_two_batches/open3d_gicp/B_batch2_refined.npz b/results/01_previous_two_batches/open3d_gicp/B_batch2_refined.npz
deleted file mode 100644
index 026f417..0000000
Binary files a/results/01_previous_two_batches/open3d_gicp/B_batch2_refined.npz and /dev/null differ
diff --git a/results/01_previous_two_batches/open3d_gicp/B_batch2_refined.refinement.json b/results/01_previous_two_batches/open3d_gicp/B_batch2_refined.refinement.json
deleted file mode 100644
index 5fca1fc..0000000
--- a/results/01_previous_two_batches/open3d_gicp/B_batch2_refined.refinement.json
+++ /dev/null
@@ -1,1289 +0,0 @@
-{
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diff --git a/results/01_previous_two_batches/open3d_gicp/batch1_auxiliary_check.json b/results/01_previous_two_batches/open3d_gicp/batch1_auxiliary_check.json
deleted file mode 100644
index ca03da5..0000000
--- a/results/01_previous_two_batches/open3d_gicp/batch1_auxiliary_check.json
+++ /dev/null
@@ -1,312 +0,0 @@
-{
-  "role": "auxiliary check only; first-batch RTK is sparse",
-  "blind_with_respect_to_X": true,
-  "note": "No AX residual was used to select these pairs",
-  "stations": 38,
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diff --git a/results/01_previous_two_batches/open3d_gicp/extrinsic_batch2.json b/results/01_previous_two_batches/open3d_gicp/extrinsic_batch2.json
deleted file mode 100644
index 1634334..0000000
--- a/results/01_previous_two_batches/open3d_gicp/extrinsic_batch2.json
+++ /dev/null
@@ -1,744 +0,0 @@
-{
-  "schema_version": 2,
-  "success": true,
-  "message": "Both `ftol` and `xtol` termination conditions are satisfied.",
-  "convention": "T_body_lidar maps raw LiDAR points into rear-axle body frame",
-  "equation": "A_ij X = X B_ij",
-  "measured_extrinsic_used_as_initial": false,
-  "translation_m": [
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-    ]
-  },
-  "bootstrap": {
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-      "pitch_deg",
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diff --git a/results/01_previous_two_batches/open3d_gicp/extrinsic_batch2_refined.json b/results/01_previous_two_batches/open3d_gicp/extrinsic_batch2_refined.json
deleted file mode 100644
index cdc3672..0000000
--- a/results/01_previous_two_batches/open3d_gicp/extrinsic_batch2_refined.json
+++ /dev/null
@@ -1,534 +0,0 @@
-{
-  "schema_version": 2,
-  "success": true,
-  "message": "Both `ftol` and `xtol` termination conditions are satisfied.",
-  "convention": "T_body_lidar maps raw LiDAR points into rear-axle body frame",
-  "equation": "A_ij X = X B_ij",
-  "measured_extrinsic_used_as_initial": false,
-  "translation_m": [
-    1.2978831677200011,
-    -0.0030997734098957433,
-    0.7217892226151688
-  ],
-  "rotation_rpy_deg_xyz": [
-    -0.7572070226288585,
-    1.1460424368859559,
-    -0.8797812288284186
-  ],
-  "quaternion_xyzw": [
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-    0.01005115598038874,
-    -0.007610830022211968,
-    0.9998991958099549
-  ],
-  "matrix_4x4": [
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-      0.015088846999329667,
-      0.020199690985244836,
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-    ],
-    [
-      0.0,
-      0.0,
-      0.0,
-      1.0
-    ]
-  ],
-  "estimation": {
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-    "pairs": 66,
-    "residuals": {
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-  },
-  "ground": {
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-    "formula": "d_lidar - (R_X n_lidar)^T t_X - body_height"
-  },
-  "linearized_one_sigma": {
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-    "warning": "conditional local estimate; bootstrap is the primary stability check"
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-  "solver_multistart": {
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-  }
-}
diff --git a/results/01_previous_two_batches/small_gicp/B_batch1_auxiliary.npz b/results/01_previous_two_batches/small_gicp/B_batch1_auxiliary.npz
deleted file mode 100644
index 9fadba4..0000000
Binary files a/results/01_previous_two_batches/small_gicp/B_batch1_auxiliary.npz and /dev/null differ
diff --git a/results/01_previous_two_batches/small_gicp/B_batch1_auxiliary_refined.npz b/results/01_previous_two_batches/small_gicp/B_batch1_auxiliary_refined.npz
deleted file mode 100644
index aaf663f..0000000
Binary files a/results/01_previous_two_batches/small_gicp/B_batch1_auxiliary_refined.npz and /dev/null differ
diff --git a/results/01_previous_two_batches/small_gicp/B_batch1_auxiliary_refined.refinement.json b/results/01_previous_two_batches/small_gicp/B_batch1_auxiliary_refined.refinement.json
deleted file mode 100644
index c617999..0000000
--- a/results/01_previous_two_batches/small_gicp/B_batch1_auxiliary_refined.refinement.json
+++ /dev/null
@@ -1,1107 +0,0 @@
-{
-  "selection_is_X_independent": true,
-  "criteria": {
-    "min_inlier_ratio": 0.7,
-    "max_inlier_rmse_m": 0.13,
-    "max_rotation_invariant_error_deg": 0.75,
-    "reverse_translation_tolerance_m": 0.05,
-    "reverse_rotation_tolerance_deg": 0.5
-  },
-  "input_pairs": 88,
-  "accepted_pairs": 36,
-  "pairs": [
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-      "j": 1,
-      "heldout_inlier_ratio": 0.7376764924448849,
-      "heldout_inlier_rmse_m": 0.11846276711125131,
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-      "reverse_rotation_deg": 0.02790414903884654,
-      "accepted": true,
-      "rejection_reasons": []
-    },
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-      "reverse_rotation_deg": 0.20055597955733165,
-      "accepted": false,
-      "rejection_reasons": [
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-      "accepted": true,
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diff --git a/results/01_previous_two_batches/small_gicp/B_batch1_quality.csv b/results/01_previous_two_batches/small_gicp/B_batch1_quality.csv
deleted file mode 100644
index 39a10cb..0000000
--- a/results/01_previous_two_batches/small_gicp/B_batch1_quality.csv
+++ /dev/null
@@ -1,109 +0,0 @@
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diff --git a/results/01_previous_two_batches/small_gicp/B_batch1_quality.json b/results/01_previous_two_batches/small_gicp/B_batch1_quality.json
deleted file mode 100644
index 22efe53..0000000
--- a/results/01_previous_two_batches/small_gicp/B_batch1_quality.json
+++ /dev/null
@@ -1,13509 +0,0 @@
-{
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-    "body": "C:\\Users\\admin\\Documents\\Codex\\2026-07-15\\wo\\outputs\\calibration_20260717\\prepared\\body_poses_rear_gga_raw_rear_to_front.csv",
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-    "quality_json": "C:\\Users\\admin\\Documents\\Codex\\2026-07-15\\wo\\rigorous_build\\results\\small_gicp\\B_batch1_quality.json",
-    "quality_csv": "C:\\Users\\admin\\Documents\\Codex\\2026-07-15\\wo\\rigorous_build\\results\\small_gicp\\B_batch1_quality.csv",
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diff --git a/results/01_previous_two_batches/small_gicp/B_batch2_estimation.npz b/results/01_previous_two_batches/small_gicp/B_batch2_estimation.npz
deleted file mode 100644
index de582af..0000000
Binary files a/results/01_previous_two_batches/small_gicp/B_batch2_estimation.npz and /dev/null differ
diff --git a/results/01_previous_two_batches/small_gicp/B_batch2_quality.csv b/results/01_previous_two_batches/small_gicp/B_batch2_quality.csv
deleted file mode 100644
index 1bd5b46..0000000
--- a/results/01_previous_two_batches/small_gicp/B_batch2_quality.csv
+++ /dev/null
@@ -1,176 +0,0 @@
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diff --git a/results/01_previous_two_batches/small_gicp/B_batch2_quality.json b/results/01_previous_two_batches/small_gicp/B_batch2_quality.json
deleted file mode 100644
index b112a9d..0000000
--- a/results/01_previous_two_batches/small_gicp/B_batch2_quality.json
+++ /dev/null
@@ -1,22523 +0,0 @@
-{
-  "schema_version": 2,
-  "backend": "small_gicp",
-  "transform_convention": "B_ij=T_Li_Lj maps station j points into station i",
-  "raw_point_field": "points_raw",
-  "measured_extrinsic_used_as_initial": false,
-  "stations": 38,
-  "candidate_pairs": 175,
-  "accepted_pairs": 154,
-  "parameters": {
-    "command": "pairs",
-    "backend": "small_gicp",
-    "frames": "C:\\Users\\admin\\Documents\\Codex\\2026-07-15\\wo\\outputs\\calibration_data1_20260720\\prepared\\frames_all",
-    "body": "C:\\Users\\admin\\Documents\\Codex\\2026-07-15\\wo\\outputs\\calibration_data1_20260720\\prepared\\body_poses_rear_gga_raw_rear_to_front.csv",
-    "output": "C:\\Users\\admin\\Documents\\Codex\\2026-07-15\\wo\\rigorous_build\\results\\small_gicp\\B_batch2_estimation.npz",
-    "quality_json": "C:\\Users\\admin\\Documents\\Codex\\2026-07-15\\wo\\rigorous_build\\results\\small_gicp\\B_batch2_quality.json",
-    "quality_csv": "C:\\Users\\admin\\Documents\\Codex\\2026-07-15\\wo\\rigorous_build\\results\\small_gicp\\B_batch2_quality.csv",
-    "time_offset": 0.0,
-    "min_stations": 30,
-    "min_pairs": 25,
-    "min_gap": 1,
-    "max_gap": 5,
-    "min_translation": 0.5,
-    "min_rotation": 3.0,
-    "min_range": 2.0,
-    "max_range": 50.0,
-    "z_min": -0.6,
-    "z_max": 5.0,
-    "min_roi_points": 1000,
-    "holdout_fraction": 0.2,
-    "voxels": [
-      0.3,
-      0.15,
-      0.08
-    ],
-    "correspondences": [
-      1.2,
-      0.5,
-      0.25
-    ],
-    "iterations": 60,
-    "threads": 8,
-    "evaluation_distance": 0.25,
-    "min_inlier_ratio": 0.35,
-    "max_inlier_rmse": 0.16,
-    "max_hessian_condition": 100000000.0,
-    "reverse_translation_tolerance": 0.08,
-    "reverse_rotation_tolerance": 0.5,
-    "multistart": 2,
-    "multistart_translation_sigma": 0.3,
-    "multistart_rotation_sigma": 3.0,
-    "multistart_translation_tolerance": 0.08,
-    "multistart_rotation_tolerance": 0.5,
-    "min_multistart_success": 0.5,
-    "seed": 20260721
-  },
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diff --git a/results/01_previous_two_batches/small_gicp/B_batch2_refined.npz b/results/01_previous_two_batches/small_gicp/B_batch2_refined.npz
deleted file mode 100644
index 74d7a01..0000000
Binary files a/results/01_previous_two_batches/small_gicp/B_batch2_refined.npz and /dev/null differ
diff --git a/results/01_previous_two_batches/small_gicp/B_batch2_refined.refinement.json b/results/01_previous_two_batches/small_gicp/B_batch2_refined.refinement.json
deleted file mode 100644
index d1121f5..0000000
--- a/results/01_previous_two_batches/small_gicp/B_batch2_refined.refinement.json
+++ /dev/null
@@ -1,1865 +0,0 @@
-{
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diff --git a/results/01_previous_two_batches/small_gicp/batch1_auxiliary_check.json b/results/01_previous_two_batches/small_gicp/batch1_auxiliary_check.json
deleted file mode 100644
index 12e6e4b..0000000
--- a/results/01_previous_two_batches/small_gicp/batch1_auxiliary_check.json
+++ /dev/null
@@ -1,277 +0,0 @@
-{
-  "role": "auxiliary check only; first-batch RTK is sparse",
-  "blind_with_respect_to_X": true,
-  "note": "No AX residual was used to select these pairs",
-  "stations": 38,
-  "metrics": {
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-      "p95": 0.14147696290683623,
-      "max": 0.15743855349684896
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-      "p90": 1.8257616608147966,
-      "p95": 1.9151501783565152,
-      "max": 2.3872345295181554
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-    "per_pair": [
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-        "i": 0,
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diff --git a/results/01_previous_two_batches/small_gicp/extrinsic_batch2.json b/results/01_previous_two_batches/small_gicp/extrinsic_batch2.json
deleted file mode 100644
index 6688257..0000000
--- a/results/01_previous_two_batches/small_gicp/extrinsic_batch2.json
+++ /dev/null
@@ -1,974 +0,0 @@
-{
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diff --git a/results/01_previous_two_batches/small_gicp/extrinsic_batch2_refined.json b/results/01_previous_two_batches/small_gicp/extrinsic_batch2_refined.json
deleted file mode 100644
index fc6b6f7..0000000
--- a/results/01_previous_two_batches/small_gicp/extrinsic_batch2_refined.json
+++ /dev/null
@@ -1,604 +0,0 @@
-{
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-          "pair_index": 67,
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-        {
-          "pair_index": 68,
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-        {
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-        {
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-        },
-        {
-          "pair_index": 77,
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-        {
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-        }
-      ]
-    }
-  },
-  "ground": {
-    "planes": 38,
-    "body_origin_height_above_ground_m": 0.2335,
-    "formula": "d_lidar - (R_X n_lidar)^T t_X - body_height"
-  },
-  "linearized_one_sigma": {
-    "translation_m": [
-      0.004217873072423743,
-      0.004428061325180952,
-      0.004921296107038976
-    ],
-    "rotation_deg": [
-      0.04989765234702571,
-      0.04568528000305764,
-      0.12720936620845405
-    ],
-    "warning": "conditional local estimate; bootstrap is the primary stability check"
-  },
-  "weighted_jacobian_condition_number": 6.329566115808833,
-  "solver_multistart": {
-    "runs": 12,
-    "candidates_relative_to_best": [
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-        "success": true,
-        "translation_m": 3.20226506801652e-10,
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-        "rotation_deg": 0.0
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-        "rotation_deg": 7.954648404736881e-08
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-  },
-  "bootstrap": {
-    "runs": 100,
-    "order": [
-      "x_m",
-      "y_m",
-      "z_m",
-      "roll_deg",
-      "pitch_deg",
-      "yaw_deg"
-    ],
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-      0.062093058432709465
-    ],
-    "p025": [
-      1.2968099294514637,
-      -0.006751632579940086,
-      0.7193267956198541,
-      -0.9300082754299475,
-      1.0287033540941326,
-      -1.0774039892205403
-    ],
-    "p975": [
-      1.302479553931627,
-      -0.0001961195897526885,
-      0.7244258625906532,
-      -0.6646157463265417,
-      1.254120304082275,
-      -0.8275267997610058
-    ]
-  }
-}
diff --git a/results/02_data4_calibration/README.md b/results/02_data4_calibration/README.md
deleted file mode 100644
index d0fcfe6..0000000
--- a/results/02_data4_calibration/README.md
+++ /dev/null
@@ -1,12 +0,0 @@
-# data4 独立标定结果
-
-data4 含 34 个静止站点，LiDAR 来自逐站 dlog，RTK/IMU 来自独立 rscap。求解不使用手量外参初始化。
-
-```text
-translation_m = [1.300376020, -0.001706691, 0.704877045]
-RPY_deg_xyz   = [-0.791891617, 1.393823210, -0.970742631]
-AX RMS        = 0.11762 m / 1.24257 deg (26 pairs)
-condition     = 7.44293
-```
-
-该结果用于独立对照，不是当前部署值。`final_extrinsic_data4.json` 与 `consensus/extrinsic.json` 数值相同；前者是便于下游读取的顶层副本。
diff --git a/results/02_data4_calibration/common/ground_planes.csv b/results/02_data4_calibration/common/ground_planes.csv
deleted file mode 100644
index 565940d..0000000
--- a/results/02_data4_calibration/common/ground_planes.csv
+++ /dev/null
@@ -1,35 +0,0 @@
-time,nx,ny,nz,d,inliers,rms_m,frame_counter
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-1784783905.353819,0.0037183584307534687,-0.006818427483323246,0.9999698409738341,0.9412842800288904,1992,0.011942807895967073,1182
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-1784784549.4274275,-0.025174259196536854,-0.013435577824823405,0.9995927880504234,0.9410339772836553,1603,0.01154746446935748,7623
-1784784614.7244046,-0.03173300872144653,-0.01870285516152855,0.9993213794202,0.932566466561638,1970,0.01233410897082844,8276
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-1784785967.8726046,-0.031038730802887403,-0.010699305087773895,0.9994609157244643,0.9511405539250901,1512,0.013166899954854165,21808
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-1784786087.9670725,-0.02720411594210121,-0.012536181034248165,0.9995512894498637,0.942804167293392,1531,0.013246549575843425,23009
-1784786160.8647907,-0.030839502708575457,0.06473269778477829,0.9974259886879789,1.0783938869067702,1436,0.010501132985089602,23738
-1784786252.6621523,-0.040972893104105006,-0.02082299858725662,0.9989432540242288,0.9524735117369321,1736,0.012945834939507173,24656
-1784786319.6581354,-0.029761355495275914,-0.026565272466750618,0.9992039571668294,0.9594371422885729,1571,0.013108184070957877,25326
-1784786396.7558627,-0.030769194030483185,-0.022645428394942407,0.9992699541522921,0.9756606317668476,1326,0.013202989492489907,26097
-1784786557.4492514,-0.019983269314458783,-0.016965365794746882,0.9996563636124948,0.9409853928234136,1228,0.013269243263785414,27704
diff --git a/results/02_data4_calibration/consensus/B_consensus.consensus.json b/results/02_data4_calibration/consensus/B_consensus.consensus.json
deleted file mode 100644
index d6f7efb..0000000
--- a/results/02_data4_calibration/consensus/B_consensus.consensus.json
+++ /dev/null
@@ -1,340 +0,0 @@
-{
-  "selection_is_X_independent": true,
-  "B_source": "Open3D; small_gicp is used only as an agreement gate",
-  "max_translation_m": 0.05,
-  "max_rotation_deg": 0.5,
-  "input_open3d_pairs": 42,
-  "accepted_pairs": 26,
-  "pairs": [
-    {
-      "i": 0,
-      "j": 1,
-      "open3d_small_translation_m": 0.014276441704401843,
-      "open3d_small_rotation_deg": 0.61360593819684,
-      "accepted": false,
-      "reason": "backend_disagreement"
-    },
-    {
-      "i": 0,
-      "j": 2,
-      "open3d_small_translation_m": 0.019952450418350955,
-      "open3d_small_rotation_deg": 0.1460927002571647,
-      "accepted": true,
-      "reason": ""
-    },
-    {
-      "i": 1,
-      "j": 2,
-      "accepted": false,
-      "reason": "not_in_small_gicp_refined"
-    },
-    {
-      "i": 2,
-      "j": 3,
-      "open3d_small_translation_m": 0.02240729290024995,
-      "open3d_small_rotation_deg": 0.16748011698659707,
-      "accepted": true,
-      "reason": ""
-    },
-    {
-      "i": 2,
-      "j": 5,
-      "open3d_small_translation_m": 0.0061616498009369,
-      "open3d_small_rotation_deg": 0.13760629005733752,
-      "accepted": true,
-      "reason": ""
-    },
-    {
-      "i": 3,
-      "j": 5,
-      "open3d_small_translation_m": 0.03979893704050873,
-      "open3d_small_rotation_deg": 0.21317157512260582,
-      "accepted": true,
-      "reason": ""
-    },
-    {
-      "i": 3,
-      "j": 6,
-      "open3d_small_translation_m": 0.012411893826144786,
-      "open3d_small_rotation_deg": 0.6409039547122976,
-      "accepted": false,
-      "reason": "backend_disagreement"
-    },
-    {
-      "i": 5,
-      "j": 8,
-      "open3d_small_translation_m": 0.02304199707639382,
-      "open3d_small_rotation_deg": 0.37075901631515606,
-      "accepted": true,
-      "reason": ""
-    },
-    {
-      "i": 6,
-      "j": 7,
-      "open3d_small_translation_m": 0.008481323658868146,
-      "open3d_small_rotation_deg": 0.2110246381252998,
-      "accepted": true,
-      "reason": ""
-    },
-    {
-      "i": 6,
-      "j": 8,
-      "open3d_small_translation_m": 0.03928926702287607,
-      "open3d_small_rotation_deg": 0.3638880951335251,
-      "accepted": true,
-      "reason": ""
-    },
-    {
-      "i": 7,
-      "j": 8,
-      "open3d_small_translation_m": 0.008121615288998074,
-      "open3d_small_rotation_deg": 0.6269514061788241,
-      "accepted": false,
-      "reason": "backend_disagreement"
-    },
-    {
-      "i": 10,
-      "j": 11,
-      "open3d_small_translation_m": 0.021311366483594964,
-      "open3d_small_rotation_deg": 0.5895827931090624,
-      "accepted": false,
-      "reason": "backend_disagreement"
-    },
-    {
-      "i": 12,
-      "j": 14,
-      "open3d_small_translation_m": 0.021593615635265958,
-      "open3d_small_rotation_deg": 0.28280557179019644,
-      "accepted": true,
-      "reason": ""
-    },
-    {
-      "i": 12,
-      "j": 15,
-      "open3d_small_translation_m": 0.03680193420722766,
-      "open3d_small_rotation_deg": 0.560849139510841,
-      "accepted": false,
-      "reason": "backend_disagreement"
-    },
-    {
-      "i": 13,
-      "j": 15,
-      "open3d_small_translation_m": 0.02340982602704091,
-      "open3d_small_rotation_deg": 0.5560478634176494,
-      "accepted": false,
-      "reason": "backend_disagreement"
-    },
-    {
-      "i": 13,
-      "j": 16,
-      "open3d_small_translation_m": 0.027602744462628358,
-      "open3d_small_rotation_deg": 0.2529072067309942,
-      "accepted": true,
-      "reason": ""
-    },
-    {
-      "i": 15,
-      "j": 16,
-      "open3d_small_translation_m": 0.0209082447077901,
-      "open3d_small_rotation_deg": 0.03400462126505844,
-      "accepted": true,
-      "reason": ""
-    },
-    {
-      "i": 15,
-      "j": 17,
-      "open3d_small_translation_m": 0.04186146133502697,
-      "open3d_small_rotation_deg": 0.13358624916951176,
-      "accepted": true,
-      "reason": ""
-    },
-    {
-      "i": 15,
-      "j": 18,
-      "open3d_small_translation_m": 0.014610177110996908,
-      "open3d_small_rotation_deg": 0.25378510251316655,
-      "accepted": true,
-      "reason": ""
-    },
-    {
-      "i": 16,
-      "j": 19,
-      "open3d_small_translation_m": 0.012703728170382652,
-      "open3d_small_rotation_deg": 0.36607447371237334,
-      "accepted": true,
-      "reason": ""
-    },
-    {
-      "i": 17,
-      "j": 18,
-      "open3d_small_translation_m": 0.03054772105829047,
-      "open3d_small_rotation_deg": 0.6293060553954827,
-      "accepted": false,
-      "reason": "backend_disagreement"
-    },
-    {
-      "i": 21,
-      "j": 22,
-      "open3d_small_translation_m": 0.008438580476457845,
-      "open3d_small_rotation_deg": 0.15351253406054555,
-      "accepted": true,
-      "reason": ""
-    },
-    {
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-      "j": 23,
-      "open3d_small_translation_m": 0.018479690388276085,
-      "open3d_small_rotation_deg": 0.5781174905909121,
-      "accepted": false,
-      "reason": "backend_disagreement"
-    },
-    {
-      "i": 21,
-      "j": 24,
-      "open3d_small_translation_m": 0.031284642427708814,
-      "open3d_small_rotation_deg": 0.39218826727895556,
-      "accepted": true,
-      "reason": ""
-    },
-    {
-      "i": 22,
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-      "open3d_small_translation_m": 0.011568269703658672,
-      "open3d_small_rotation_deg": 0.06135783639322868,
-      "accepted": true,
-      "reason": ""
-    },
-    {
-      "i": 22,
-      "j": 25,
-      "open3d_small_translation_m": 0.041018828349300214,
-      "open3d_small_rotation_deg": 0.42033964239927313,
-      "accepted": true,
-      "reason": ""
-    },
-    {
-      "i": 23,
-      "j": 24,
-      "open3d_small_translation_m": 0.009191025383393128,
-      "open3d_small_rotation_deg": 0.5691342385312416,
-      "accepted": false,
-      "reason": "backend_disagreement"
-    },
-    {
-      "i": 25,
-      "j": 26,
-      "open3d_small_translation_m": 0.020915300595375722,
-      "open3d_small_rotation_deg": 0.48750667250286367,
-      "accepted": true,
-      "reason": ""
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\ No newline at end of file
diff --git a/results/02_data4_calibration/consensus/B_consensus.npz b/results/02_data4_calibration/consensus/B_consensus.npz
deleted file mode 100644
index 251bd12..0000000
Binary files a/results/02_data4_calibration/consensus/B_consensus.npz and /dev/null differ
diff --git a/results/02_data4_calibration/consensus/extrinsic.json b/results/02_data4_calibration/consensus/extrinsic.json
deleted file mode 100644
index 2bfd4ce..0000000
--- a/results/02_data4_calibration/consensus/extrinsic.json
+++ /dev/null
@@ -1,334 +0,0 @@
-{
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\ No newline at end of file
diff --git a/results/02_data4_calibration/final_extrinsic_data4.json b/results/02_data4_calibration/final_extrinsic_data4.json
deleted file mode 100644
index 2bfd4ce..0000000
--- a/results/02_data4_calibration/final_extrinsic_data4.json
+++ /dev/null
@@ -1,334 +0,0 @@
-{
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\ No newline at end of file
diff --git a/results/02_data4_calibration/open3d_gicp/B_estimation.npz b/results/02_data4_calibration/open3d_gicp/B_estimation.npz
deleted file mode 100644
index 58cec4e..0000000
Binary files a/results/02_data4_calibration/open3d_gicp/B_estimation.npz and /dev/null differ
diff --git a/results/02_data4_calibration/open3d_gicp/B_quality.csv b/results/02_data4_calibration/open3d_gicp/B_quality.csv
deleted file mode 100644
index 96d43b5..0000000
--- a/results/02_data4_calibration/open3d_gicp/B_quality.csv
+++ /dev/null
@@ -1,97 +0,0 @@
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-25,27,1.7666235781584831,68.22877288971053,0.8510739856801909,0.10418150333394147,6,2.368253417089997,0.006103232696002816,0.13366555345652814,1.0,True,
-25,28,2.1807182972588706,88.09106909546726,0.8853518429870751,0.10761251229652005,6,2.6372860976794645,0.003483231665912094,0.0369774420199415,1.0,True,
-26,27,0.6269948654714946,25.284375303243706,0.9183867141162515,0.09074909570650921,6,2.8142315359282506,0.00040199505815422204,0.011554314408129918,1.0,True,
-26,28,0.9431372257108486,45.14667150900044,0.8853200095170116,0.10604184939655073,6,2.656402027789519,0.007320240476189879,0.12930335868605478,1.0,True,
-26,29,1.129925637779203,87.41573662125148,0.7880466815984911,0.10871274240898265,6,3.111957466886604,0.0063952430610542755,0.039517035902874385,1.0,True,
-27,28,0.44809323479571145,19.862296205756735,0.9289448669201521,0.0850509551532673,6,2.96325286846982,0.005157655135591474,0.022666807877311387,1.0,True,
-27,29,1.160064136065596,62.13136131800778,0.7872365477452019,0.10455513464835667,6,2.9621627623005296,0.011650639607012138,0.1624719134077532,1.0,True,
-27,30,4.25412615059095,152.09392556214777,0.04792444029850746,0.15706827084964883,6,3.4115087753552786,2.5641513880069633,2.874944882076104,0.0,False,heldout_inlier_ratio;forward_reverse_translation;forward_reverse_rotation;multistart_instability
-28,29,1.5995723610319212,42.26906511225104,0.8000944621560987,0.1086547547358129,6,3.1466224100058553,0.0011394164967304414,0.02119627748719656,1.0,True,
-28,30,4.295353381127667,132.23162935639104,0.042095416276894296,0.16025490727880456,6,4.631028587407634,2.5607552487652696,2.17230408479254,0.0,False,heldout_inlier_ratio;heldout_inlier_rmse;forward_reverse_translation;forward_reverse_rotation;multistart_instability
-28,31,5.754426930327516,158.8421298011293,0.7465330381074466,0.1066966653439246,6,2.402598366822474,0.00635764905956918,0.040016615214377715,1.0,True,
-29,30,4.099530130205247,89.96256424413995,0.7248812145092132,0.10870831469083347,6,2.9471223804737057,0.00465638537716095,0.12465763189227934,1.0,True,
-29,31,4.890018768530818,116.57306468887772,0.7243012243012243,0.11138751941762699,6,2.7645021322697017,0.004263906321896464,0.046637396086304225,1.0,True,
-29,32,4.464737187763289,159.39493219688632,0.6956070563818748,0.1103354081949904,6,3.227012588611917,0.011088061861347823,0.34561739459504637,1.0,True,
-30,31,2.3862917603439455,26.61050044473775,0.8185562292643862,0.0961579573295129,6,2.899558208444643,0.004999163455591531,0.0213847958734735,1.0,True,
-30,32,1.1507634071714652,69.43236795274659,0.8041343079031521,0.099533431536842,6,2.6146168742247573,0.003171376495143,0.02376737774843464,1.0,True,
-30,33,2.4361832484951105,160.7145717128102,0.0824534345711235,0.13003518012314966,6,7.2913036106936,1.3743823383381788,1.9837113244583153,0.0,False,heldout_inlier_ratio;forward_reverse_translation;forward_reverse_rotation;multistart_instability
-31,32,1.2514382602180638,42.82186750800885,0.8157085941946499,0.09925944770258267,6,3.0485411400768245,0.004719596234887584,0.06146741991681224,1.0,True,
-31,33,0.641507519046697,134.10407126807203,0.0911563017261764,0.12702324561674966,6,7.541483837366941,2.816294381538612,3.333105317420589,0.0,False,heldout_inlier_ratio;forward_reverse_translation;forward_reverse_rotation;multistart_instability
-32,33,1.4370687242949811,91.2822037600631,0.7569928006609229,0.10008740880870744,6,3.6611044282667207,2.988193350509204,2.696443494598379,1.0,False,forward_reverse_translation;forward_reverse_rotation
diff --git a/results/02_data4_calibration/open3d_gicp/B_quality.json b/results/02_data4_calibration/open3d_gicp/B_quality.json
deleted file mode 100644
index 8a1a178..0000000
--- a/results/02_data4_calibration/open3d_gicp/B_quality.json
+++ /dev/null
@@ -1,12004 +0,0 @@
-{
-  "schema_version": 2,
-  "backend": "open3d",
-  "transform_convention": "B_ij=T_Li_Lj maps station j points into station i",
-  "raw_point_field": "points_raw",
-  "measured_extrinsic_used_as_initial": false,
-  "stations": 34,
-  "candidate_pairs": 96,
-  "accepted_pairs": 87,
-  "parameters": {
-    "command": "pairs",
-    "backend": "open3d",
-    "frames": "<external-data>\\data4_prepared\\frames_all",
-    "body": "<external-data>\\data4_prepared\\body_poses_rear_gga_raw_rear_to_front.csv",
-    "output": "results\\02_data4_calibration\\open3d_gicp\\B_estimation.npz",
-    "quality_json": "results\\02_data4_calibration\\open3d_gicp\\B_quality.json",
-    "quality_csv": "results\\02_data4_calibration\\open3d_gicp\\B_quality.csv",
-    "time_offset": 0.0,
-    "min_stations": 30,
-    "min_pairs": 20,
-    "min_gap": 1,
-    "max_gap": 3,
-    "min_translation": 0.5,
-    "min_rotation": 3.0,
-    "min_range": 2.0,
-    "max_range": 50.0,
-    "z_min": -0.6,
-    "z_max": 5.0,
-    "min_roi_points": 1000,
-    "holdout_fraction": 0.2,
-    "voxels": [
-      0.3,
-      0.15,
-      0.08
-    ],
-    "correspondences": [
-      1.2,
-      0.5,
-      0.25
-    ],
-    "iterations": 40,
-    "threads": 8,
-    "evaluation_distance": 0.25,
-    "min_inlier_ratio": 0.35,
-    "max_inlier_rmse": 0.16,
-    "max_hessian_condition": 100000000.0,
-    "reverse_translation_tolerance": 0.08,
-    "reverse_rotation_tolerance": 0.5,
-    "multistart": 1,
-    "multistart_translation_sigma": 0.3,
-    "multistart_rotation_sigma": 3.0,
-    "multistart_translation_tolerance": 0.08,
-    "multistart_rotation_tolerance": 0.5,
-    "min_multistart_success": 0.5,
-    "seed": 20260721
-  },
-  "accepted_loop_closure": {
-    "count": 80,
-    "translation_rms_m": 0.018166280559552293,
-    "translation_p95_m": 0.032032870276120416,
-    "rotation_rms_deg": 0.2258764385588969,
-    "rotation_p95_deg": 0.4138842730797386
-  },
-  "pairs": [
-    {
-      "i": 0,
-      "j": 1,
-      "lidar_time_i": 1784783825.357129,
-      "lidar_time_j": 1784783905.353819,
-      "frame_counter_i": 382,
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-      "rtk_rotation_deg": 24.171297449440786,
-      "nearest_rtk_dt_i_s": 0.0,
-      "nearest_rtk_dt_j_s": 0.0,
-      "initial_B_source": "X0=identity; B0=A (no measured extrinsic)",
-      "B_ij_4x4": [
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-          0.9124833454993864,
-          0.4087832678693191,
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-          1.607248674769736
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-          0.015083257286964366
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-          0.0,
-          0.0,
-          1.0
-        ]
-      ],
-      "backend": "open3d",
-      "backend_converged": null,
-      "backend_iterations": null,
-      "backend_num_inliers": 8912,
-      "backend_objective": 121.7846872438052,
-      "backend_elapsed_sec": 0.6735248000186402,
-      "multiscale_stages": [
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-          "max_correspondence_m": 1.2,
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-          "source_points": 4745
-        },
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-          "max_correspondence_m": 0.5,
-          "fitness": 0.9067073170731708,
-          "inlier_rmse_m": 0.17788239925150534,
-          "target_points": 8116,
-          "source_points": 8200
-        },
-        {
-          "voxel_m": 0.08,
-          "max_correspondence_m": 0.25,
-          "fitness": 0.7850599013389711,
-          "inlier_rmse_m": 0.11689845025056375,
-          "target_points": 11527,
-          "source_points": 11352
-        }
-      ],
-      "heldout_symmetric": {
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-        "inliers": 6276,
-        "inlier_ratio": 0.8061657032755298,
-        "inlier_rmse_m": 0.10961296014103376,
-        "median_m": 0.10290553406024071,
-        "p90_m": 0.4159689941694349,
-        "p95_m": 0.660543787598926
-      },
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-        "native_order": [
-          "rx_rad",
-          "ry_rad",
-          "rz_rad",
-          "tx_m",
-          "ty_m",
-          "tz_m"
-        ],
-        "scaled_eigenvalues": [
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-        "effective_rank": 6,
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-        "rotation_deg": 0.15304490677206398
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-        "success_rate": 1.0,
-        "deltas": [
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-            "rotation_deg": 3.644959732437771e-14
-          }
-        ]
-      },
-      "accepted": true,
-      "rejection_reasons": []
-    },
-    {
-      "i": 0,
-      "j": 2,
-      "lidar_time_i": 1784783825.357129,
-      "lidar_time_j": 1784783971.0503054,
-      "frame_counter_i": 382,
-      "frame_counter_j": 1839,
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-      "rtk_rotation_deg": 80.09074797031298,
-      "nearest_rtk_dt_i_s": 0.0,
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-      "initial_B_source": "X0=identity; B0=A (no measured extrinsic)",
-      "B_ij_4x4": [
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-          0.18415074469542553,
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-          -0.004560979739464177,
-          0.1285797386588232
-        ],
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-          0.18384945289183605,
-          -0.037986359574273536,
-          -3.6632910616894554
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-          0.0,
-          0.0,
-          1.0
-        ]
-      ],
-      "backend": "open3d",
-      "backend_converged": null,
-      "backend_iterations": null,
-      "backend_num_inliers": 8376,
-      "backend_objective": 121.70157639854357,
-      "backend_elapsed_sec": 1.1375933999952395,
-      "multiscale_stages": [
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-          "max_correspondence_m": 1.2,
-          "fitness": 0.9193615257048093,
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-          "source_points": 4824
-        },
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-            "rotation_deg": 5.017501916348629e-09
-          }
-        ]
-      },
-      "accepted": true,
-      "rejection_reasons": []
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-      "j": 33,
-      "lidar_time_i": 1784786319.6581354,
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-      "frame_counter_i": 25326,
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-      "rtk_rotation_deg": 134.10407126807203,
-      "nearest_rtk_dt_i_s": 0.0,
-      "nearest_rtk_dt_j_s": 0.0,
-      "initial_B_source": "X0=identity; B0=A (no measured extrinsic)",
-      "B_ij_4x4": [
-        [
-          -0.6933790222488846,
-          0.7198797992021888,
-          0.031600731095929126,
-          0.30033073323356396
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-          1.031248314724261
-        ],
-        [
-          0.0,
-          0.0,
-          0.0,
-          1.0
-        ]
-      ],
-      "backend": "open3d",
-      "backend_converged": null,
-      "backend_iterations": null,
-      "backend_num_inliers": 922,
-      "backend_objective": 17.384443340953343,
-      "backend_elapsed_sec": 1.071740299987141,
-      "multiscale_stages": [
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-          "voxel_m": 0.3,
-          "max_correspondence_m": 1.2,
-          "fitness": 0.2789183775663495,
-          "inlier_rmse_m": 0.7592150008800915,
-          "target_points": 4233,
-          "source_points": 3994
-        },
-        {
-          "voxel_m": 0.15,
-          "max_correspondence_m": 0.5,
-          "fitness": 0.11837134462012033,
-          "inlier_rmse_m": 0.288204181433143,
-          "target_points": 7861,
-          "source_points": 7147
-        },
-        {
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-          "fitness": 0.08817060342354403,
-          "inlier_rmse_m": 0.137314036505466,
-          "target_points": 11516,
-          "source_points": 10457
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-      ],
-      "heldout_symmetric": {
-        "evaluated": 8458,
-        "inliers": 771,
-        "inlier_ratio": 0.0911563017261764,
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-        "p95_m": 2.99612947209192
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-      "hessian": {
-        "native_order": [
-          "rx_rad",
-          "ry_rad",
-          "rz_rad",
-          "tx_m",
-          "ty_m",
-          "tz_m"
-        ],
-        "scaled_eigenvalues": [
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-          279.85523956074167,
-          922.0,
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-          954.7661331450001
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-        "scaled_condition_number": 7.541483837366941,
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-          -0.13999877449576664
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-        "success_rate": 0.0,
-        "deltas": [
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-            "rotation_deg": 3.358304138889011
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-      "rejection_reasons": [
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-        "forward_reverse_translation",
-        "forward_reverse_rotation",
-        "multistart_instability"
-      ]
-    },
-    {
-      "i": 32,
-      "j": 33,
-      "lidar_time_i": 1784786396.7558627,
-      "lidar_time_j": 1784786557.4492514,
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-      "rtk_rotation_deg": 91.2822037600631,
-      "nearest_rtk_dt_i_s": 0.0,
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-      "initial_B_source": "X0=identity; B0=A (no measured extrinsic)",
-      "B_ij_4x4": [
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-        ],
-        [
-          0.0,
-          0.0,
-          0.0,
-          1.0
-        ]
-      ],
-      "backend": "open3d",
-      "backend_converged": null,
-      "backend_iterations": null,
-      "backend_num_inliers": 7170,
-      "backend_objective": 92.68266713845796,
-      "backend_elapsed_sec": 1.1681094999948982,
-      "multiscale_stages": [
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-          "target_points": 4089,
-          "source_points": 3994
-        },
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-          "voxel_m": 0.15,
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-          "fitness": 0.7554218553239122,
-          "inlier_rmse_m": 0.18476958522923292,
-          "target_points": 7422,
-          "source_points": 7147
-        },
-        {
-          "voxel_m": 0.08,
-          "max_correspondence_m": 0.25,
-          "fitness": 0.6856651047145452,
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-          "target_points": 10913,
-          "source_points": 10457
-        }
-      ],
-      "heldout_symmetric": {
-        "evaluated": 8473,
-        "inliers": 6414,
-        "inlier_ratio": 0.7569928006609229,
-        "inlier_rmse_m": 0.10008740880870744,
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-        "p90_m": 0.9960371547843112,
-        "p95_m": 2.5088898917980305
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-      "hessian": {
-        "native_order": [
-          "rx_rad",
-          "ry_rad",
-          "rz_rad",
-          "tx_m",
-          "ty_m",
-          "tz_m"
-        ],
-        "scaled_eigenvalues": [
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-          9999.939188218461
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-        "effective_rank": 6,
-        "scaled_condition_number": 3.6611044282667207,
-        "weakest_scaled_direction": [
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-          0.6605258105471334,
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-          -0.04340562970352462,
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-          -0.4364897854863681
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-      "forward_reverse": {
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-        "deltas": [
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-            "translation_m": 1.826405982230485e-15,
-            "rotation_deg": 1.038543983377488e-14
-          }
-        ]
-      },
-      "accepted": false,
-      "rejection_reasons": [
-        "forward_reverse_translation",
-        "forward_reverse_rotation"
-      ]
-    }
-  ]
-}
\ No newline at end of file
diff --git a/results/02_data4_calibration/open3d_gicp/B_refined.npz b/results/02_data4_calibration/open3d_gicp/B_refined.npz
deleted file mode 100644
index 0d80e89..0000000
Binary files a/results/02_data4_calibration/open3d_gicp/B_refined.npz and /dev/null differ
diff --git a/results/02_data4_calibration/open3d_gicp/B_refined.refinement.json b/results/02_data4_calibration/open3d_gicp/B_refined.refinement.json
deleted file mode 100644
index e66ee06..0000000
--- a/results/02_data4_calibration/open3d_gicp/B_refined.refinement.json
+++ /dev/null
@@ -1,1072 +0,0 @@
-{
-  "selection_is_X_independent": true,
-  "criteria": {
-    "min_inlier_ratio": 0.7,
-    "max_inlier_rmse_m": 0.13,
-    "max_rotation_invariant_error_deg": 0.75,
-    "reverse_translation_tolerance_m": 0.05,
-    "reverse_rotation_tolerance_deg": 0.5
-  },
-  "input_pairs": 87,
-  "accepted_pairs": 42,
-  "pairs": [
-    {
-      "i": 0,
-      "j": 1,
-      "heldout_inlier_ratio": 0.8061657032755298,
-      "heldout_inlier_rmse_m": 0.10961296014103376,
-      "rotation_invariant_error_deg": 0.021953694767613996,
-      "reverse_translation_m": 0.004225163540003135,
-      "reverse_rotation_deg": 0.15304490677206398,
-      "accepted": true,
-      "rejection_reasons": []
-    },
-    {
-      "i": 0,
-      "j": 2,
-      "heldout_inlier_ratio": 0.7489394523717702,
-      "heldout_inlier_rmse_m": 0.116305716193008,
-      "rotation_invariant_error_deg": 0.6722513635970557,
-      "reverse_translation_m": 0.02073003109723772,
-      "reverse_rotation_deg": 0.12418344306820694,
-      "accepted": true,
-      "rejection_reasons": []
-    },
-    {
-      "i": 0,
-      "j": 3,
-      "heldout_inlier_ratio": 0.6310283235519265,
-      "heldout_inlier_rmse_m": 0.12470979645173065,
-      "rotation_invariant_error_deg": 0.31955029067046326,
-      "reverse_translation_m": 0.02154775870989581,
-      "reverse_rotation_deg": 0.2539904497958252,
-      "accepted": false,
-      "rejection_reasons": [
-        "overlap_ratio"
-      ]
-    },
-    {
-      "i": 1,
-      "j": 2,
-      "heldout_inlier_ratio": 0.7867383512544803,
-      "heldout_inlier_rmse_m": 0.11079021393934936,
-      "rotation_invariant_error_deg": 0.6532823847336076,
-      "reverse_translation_m": 0.0076823267394430066,
-      "reverse_rotation_deg": 0.05080433004685343,
-      "accepted": true,
-      "rejection_reasons": []
-    },
-    {
-      "i": 1,
-      "j": 3,
-      "heldout_inlier_ratio": 0.6794562317367552,
-      "heldout_inlier_rmse_m": 0.1190716913809658,
-      "rotation_invariant_error_deg": 0.28968149037614666,
-      "reverse_translation_m": 0.024832426027852336,
-      "reverse_rotation_deg": 0.29364033194785566,
-      "accepted": false,
-      "rejection_reasons": [
-        "overlap_ratio"
-      ]
-    },
-    {
-      "i": 1,
-      "j": 4,
-      "heldout_inlier_ratio": 0.6786112833230006,
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-      "rotation_invariant_error_deg": 0.2350920621707786,
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-      "reverse_rotation_deg": 0.07270245476793177,
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-      "rejection_reasons": [
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-      ]
-    },
-    {
-      "i": 2,
-      "j": 3,
-      "heldout_inlier_ratio": 0.7586776859504132,
-      "heldout_inlier_rmse_m": 0.11541610277862563,
-      "rotation_invariant_error_deg": 0.06385020919199477,
-      "reverse_translation_m": 0.007879904085793275,
-      "reverse_rotation_deg": 0.11659483159946175,
-      "accepted": true,
-      "rejection_reasons": []
-    },
-    {
-      "i": 2,
-      "j": 4,
-      "heldout_inlier_ratio": 0.7854572527608884,
-      "heldout_inlier_rmse_m": 0.1098649389241601,
-      "rotation_invariant_error_deg": 0.8714733340458736,
-      "reverse_translation_m": 0.017042953274278242,
-      "reverse_rotation_deg": 0.09383247792992147,
-      "accepted": false,
-      "rejection_reasons": [
-        "rotation_conjugacy_invariant"
-      ]
-    },
-    {
-      "i": 2,
-      "j": 5,
-      "heldout_inlier_ratio": 0.7074574574574575,
-      "heldout_inlier_rmse_m": 0.11912871456224478,
-      "rotation_invariant_error_deg": 0.18237928888538768,
-      "reverse_translation_m": 0.016641241123247028,
-      "reverse_rotation_deg": 0.24777402858141082,
-      "accepted": true,
-      "rejection_reasons": []
-    },
-    {
-      "i": 3,
-      "j": 4,
-      "heldout_inlier_ratio": 0.6974624291697462,
-      "heldout_inlier_rmse_m": 0.1172763088894914,
-      "rotation_invariant_error_deg": 0.490243673582313,
-      "reverse_translation_m": 0.012148721219467648,
-      "reverse_rotation_deg": 0.2079308684382429,
-      "accepted": false,
-      "rejection_reasons": [
-        "overlap_ratio"
-      ]
-    },
-    {
-      "i": 3,
-      "j": 5,
-      "heldout_inlier_ratio": 0.7962985964476462,
-      "heldout_inlier_rmse_m": 0.10646082199215777,
-      "rotation_invariant_error_deg": 0.552273782508431,
-      "reverse_translation_m": 0.011008298723511818,
-      "reverse_rotation_deg": 0.08217077610411756,
-      "accepted": true,
-      "rejection_reasons": []
-    },
-    {
-      "i": 3,
-      "j": 6,
-      "heldout_inlier_ratio": 0.8376509054325956,
-      "heldout_inlier_rmse_m": 0.10956583416752592,
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-      "reverse_translation_m": 0.001222821038316072,
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-      "accepted": true,
-      "rejection_reasons": []
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-    {
-      "i": 4,
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-      "accepted": false,
-      "rejection_reasons": [
-        "overlap_ratio",
-        "rotation_conjugacy_invariant"
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-    },
-    {
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-      "rejection_reasons": [
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-    },
-    {
-      "i": 4,
-      "j": 7,
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-      "rejection_reasons": [
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-    },
-    {
-      "i": 5,
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-      "heldout_inlier_ratio": 0.7526921648718901,
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-      "rotation_invariant_error_deg": 0.8049600839827704,
-      "reverse_translation_m": 0.012374747586501101,
-      "reverse_rotation_deg": 0.14461856068326442,
-      "accepted": false,
-      "rejection_reasons": [
-        "rotation_conjugacy_invariant"
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-    },
-    {
-      "i": 5,
-      "j": 7,
-      "heldout_inlier_ratio": 0.7833561729164071,
-      "heldout_inlier_rmse_m": 0.11683079277948674,
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-      "reverse_translation_m": 0.0136898748124479,
-      "reverse_rotation_deg": 0.2000656277647698,
-      "accepted": false,
-      "rejection_reasons": [
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-      ]
-    },
-    {
-      "i": 5,
-      "j": 8,
-      "heldout_inlier_ratio": 0.7410703250525275,
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-      "reverse_translation_m": 0.020336999081352437,
-      "reverse_rotation_deg": 0.07548452187379719,
-      "accepted": true,
-      "rejection_reasons": []
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-    {
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-    {
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-      "reverse_rotation_deg": 0.11752836996157842,
-      "accepted": true,
-      "rejection_reasons": []
-    },
-    {
-      "i": 6,
-      "j": 9,
-      "heldout_inlier_ratio": 0.6071384156199477,
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-      "rotation_invariant_error_deg": 0.06220808914818576,
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-      "reverse_rotation_deg": 0.4345945520890901,
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-      "rejection_reasons": [
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-    {
-      "i": 7,
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-      "accepted": true,
-      "rejection_reasons": []
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-    {
-      "i": 7,
-      "j": 9,
-      "heldout_inlier_ratio": 0.6188509200150206,
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-      "reverse_translation_m": 0.026230622734929154,
-      "reverse_rotation_deg": 0.28112746782878123,
-      "accepted": false,
-      "rejection_reasons": [
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-    },
-    {
-      "i": 7,
-      "j": 10,
-      "heldout_inlier_ratio": 0.5757088027733069,
-      "heldout_inlier_rmse_m": 0.1313446077529101,
-      "rotation_invariant_error_deg": 0.08805329493384306,
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-      "reverse_rotation_deg": 0.2297418063823675,
-      "accepted": false,
-      "rejection_reasons": [
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-        "heldout_rmse"
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-    },
-    {
-      "i": 8,
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-      "heldout_inlier_ratio": 0.6326834719980131,
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-      "heldout_inlier_rmse_m": 0.0958142916589384,
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-      "reverse_translation_m": 0.003534148840172682,
-      "reverse_rotation_deg": 0.018440169300173608,
-      "accepted": true,
-      "rejection_reasons": []
-    },
-    {
-      "i": 25,
-      "j": 27,
-      "heldout_inlier_ratio": 0.8510739856801909,
-      "heldout_inlier_rmse_m": 0.10418150333394147,
-      "rotation_invariant_error_deg": 0.24124343828054862,
-      "reverse_translation_m": 0.006103232696002816,
-      "reverse_rotation_deg": 0.13366555345652814,
-      "accepted": true,
-      "rejection_reasons": []
-    },
-    {
-      "i": 25,
-      "j": 28,
-      "heldout_inlier_ratio": 0.8853518429870751,
-      "heldout_inlier_rmse_m": 0.10761251229652005,
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-      "reverse_translation_m": 0.003483231665912094,
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-      "accepted": true,
-      "rejection_reasons": []
-    },
-    {
-      "i": 26,
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-      "reverse_rotation_deg": 0.011554314408129918,
-      "accepted": true,
-      "rejection_reasons": []
-    },
-    {
-      "i": 26,
-      "j": 28,
-      "heldout_inlier_ratio": 0.8853200095170116,
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-      "reverse_translation_m": 0.007320240476189879,
-      "reverse_rotation_deg": 0.12930335868605478,
-      "accepted": true,
-      "rejection_reasons": []
-    },
-    {
-      "i": 26,
-      "j": 29,
-      "heldout_inlier_ratio": 0.7880466815984911,
-      "heldout_inlier_rmse_m": 0.10871274240898265,
-      "rotation_invariant_error_deg": 0.6273264323501735,
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-      "accepted": true,
-      "rejection_reasons": []
-    },
-    {
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-    {
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-    {
-      "i": 28,
-      "j": 29,
-      "heldout_inlier_ratio": 0.8000944621560987,
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-      "accepted": true,
-      "rejection_reasons": []
-    },
-    {
-      "i": 28,
-      "j": 31,
-      "heldout_inlier_ratio": 0.7465330381074466,
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-      "rejection_reasons": []
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-    {
-      "i": 29,
-      "j": 30,
-      "heldout_inlier_ratio": 0.7248812145092132,
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-      "reverse_translation_m": 0.00465638537716095,
-      "reverse_rotation_deg": 0.12465763189227934,
-      "accepted": true,
-      "rejection_reasons": []
-    },
-    {
-      "i": 29,
-      "j": 31,
-      "heldout_inlier_ratio": 0.7243012243012243,
-      "heldout_inlier_rmse_m": 0.11138751941762699,
-      "rotation_invariant_error_deg": 0.6006586352807659,
-      "reverse_translation_m": 0.004263906321896464,
-      "reverse_rotation_deg": 0.046637396086304225,
-      "accepted": true,
-      "rejection_reasons": []
-    },
-    {
-      "i": 29,
-      "j": 32,
-      "heldout_inlier_ratio": 0.6956070563818748,
-      "heldout_inlier_rmse_m": 0.1103354081949904,
-      "rotation_invariant_error_deg": 0.7369667173371113,
-      "reverse_translation_m": 0.011088061861347823,
-      "reverse_rotation_deg": 0.34561739459504637,
-      "accepted": false,
-      "rejection_reasons": [
-        "overlap_ratio"
-      ]
-    },
-    {
-      "i": 30,
-      "j": 31,
-      "heldout_inlier_ratio": 0.8185562292643862,
-      "heldout_inlier_rmse_m": 0.0961579573295129,
-      "rotation_invariant_error_deg": 0.6089207032237525,
-      "reverse_translation_m": 0.004999163455591531,
-      "reverse_rotation_deg": 0.0213847958734735,
-      "accepted": true,
-      "rejection_reasons": []
-    },
-    {
-      "i": 30,
-      "j": 32,
-      "heldout_inlier_ratio": 0.8041343079031521,
-      "heldout_inlier_rmse_m": 0.099533431536842,
-      "rotation_invariant_error_deg": 0.7410181887106546,
-      "reverse_translation_m": 0.003171376495143,
-      "reverse_rotation_deg": 0.02376737774843464,
-      "accepted": true,
-      "rejection_reasons": []
-    },
-    {
-      "i": 31,
-      "j": 32,
-      "heldout_inlier_ratio": 0.8157085941946499,
-      "heldout_inlier_rmse_m": 0.09925944770258267,
-      "rotation_invariant_error_deg": 0.1261576421595052,
-      "reverse_translation_m": 0.004719596234887584,
-      "reverse_rotation_deg": 0.06146741991681224,
-      "accepted": true,
-      "rejection_reasons": []
-    }
-  ]
-}
\ No newline at end of file
diff --git a/results/02_data4_calibration/open3d_gicp/extrinsic.json b/results/02_data4_calibration/open3d_gicp/extrinsic.json
deleted file mode 100644
index e0fae03..0000000
--- a/results/02_data4_calibration/open3d_gicp/extrinsic.json
+++ /dev/null
@@ -1,414 +0,0 @@
-{
-  "schema_version": 2,
-  "success": true,
-  "message": "`ftol` termination condition is satisfied.",
-  "convention": "T_body_lidar maps raw LiDAR points into rear-axle body frame",
-  "equation": "A_ij X = X B_ij",
-  "measured_extrinsic_used_as_initial": false,
-  "translation_m": [
-    1.2975484155117711,
-    -0.0014693441955134902,
-    0.7052088406121522
-  ],
-  "rotation_rpy_deg_xyz": [
-    -0.8301548470744382,
-    1.3787117674135543,
-    -0.9873301733452331
-  ],
-  "quaternion_xyzw": [
-    -0.007139952974435751,
-    0.012092890421885221,
-    -0.008527968948116832,
-    0.9998650192992987
-  ],
-  "matrix_4x4": [
-    [
-      0.9995620714937284,
-      0.01688095033591077,
-      0.02430429482463916,
-      1.2975484155117711
-    ],
-    [
-      -0.017226321011659856,
-      0.9997525896342856,
-      0.014071722849138928,
-      -0.0014693441955134902
-    ],
-    [
-      -0.024060737635611132,
-      -0.014484234025182223,
-      0.9996055661455342,
-      0.7052088406121522
-    ],
-    [
-      0.0,
-      0.0,
-      0.0,
-      1.0
-    ]
-  ],
-  "estimation": {
-    "stations": 34,
-    "pairs": 42,
-    "residuals": {
-      "pairs": 42,
-      "translation_m": {
-        "rms": 0.12183423858445137,
-        "median": 0.060649486998667235,
-        "p90": 0.11912435755512873,
-        "p95": 0.3030566180355447,
-        "max": 0.45978165540815585
-      },
-      "rotation_deg": {
-        "rms": 1.0805282705084651,
-        "median": 0.7524132662595089,
-        "p90": 1.482445248533153,
-        "p95": 1.8550286425106393,
-        "max": 4.3358524167513774
-      },
-      "per_pair": [
-        {
-          "pair_index": 0,
-          "translation_m": 0.038624527608401314,
-          "rotation_deg": 0.8023305035396044
-        },
-        {
-          "pair_index": 1,
-          "translation_m": 0.04180287320767011,
-          "rotation_deg": 0.6893264946463747
-        },
-        {
-          "pair_index": 2,
-          "translation_m": 0.019127950093528003,
-          "rotation_deg": 1.0042991942789465
-        },
-        {
-          "pair_index": 3,
-          "translation_m": 0.06137084310587195,
-          "rotation_deg": 0.3949193126839051
-        },
-        {
-          "pair_index": 4,
-          "translation_m": 0.1071111410675142,
-          "rotation_deg": 0.29878675978634545
-        },
-        {
-          "pair_index": 5,
-          "translation_m": 0.06364016847596804,
-          "rotation_deg": 0.5544336747047969
-        },
-        {
-          "pair_index": 6,
-          "translation_m": 0.06293697736756677,
-          "rotation_deg": 0.5686016770604462
-        },
-        {
-          "pair_index": 7,
-          "translation_m": 0.024970034635953178,
-          "rotation_deg": 0.5027938164737027
-        },
-        {
-          "pair_index": 8,
-          "translation_m": 0.06609908977135717,
-          "rotation_deg": 0.769573579451918
-        },
-        {
-          "pair_index": 9,
-          "translation_m": 0.015198604597359418,
-          "rotation_deg": 0.7395239518119227
-        },
-        {
-          "pair_index": 10,
-          "translation_m": 0.08603113369700931,
-          "rotation_deg": 0.38160978353264396
-        },
-        {
-          "pair_index": 11,
-          "translation_m": 0.023734833308603348,
-          "rotation_deg": 0.5279761588421565
-        },
-        {
-          "pair_index": 12,
-          "translation_m": 0.044728554479905425,
-          "rotation_deg": 0.8691250339782107
-        },
-        {
-          "pair_index": 13,
-          "translation_m": 0.07088160554682986,
-          "rotation_deg": 0.450151294217732
-        },
-        {
-          "pair_index": 14,
-          "translation_m": 0.08888554602585935,
-          "rotation_deg": 0.6592285262192215
-        },
-        {
-          "pair_index": 15,
-          "translation_m": 0.05233056995457292,
-          "rotation_deg": 1.8589142482602727
-        },
-        {
-          "pair_index": 16,
-          "translation_m": 0.12686760514047216,
-          "rotation_deg": 1.9773175636228766
-        },
-        {
-          "pair_index": 17,
-          "translation_m": 0.06853778836627006,
-          "rotation_deg": 0.2507622154612463
-        },
-        {
-          "pair_index": 18,
-          "translation_m": 0.0613281598931951,
-          "rotation_deg": 0.3396141740929532
-        },
-        {
-          "pair_index": 19,
-          "translation_m": 0.03461219125828727,
-          "rotation_deg": 0.5120113019840405
-        },
-        {
-          "pair_index": 20,
-          "translation_m": 0.003516478473153868,
-          "rotation_deg": 0.3641614482709119
-        },
-        {
-          "pair_index": 21,
-          "translation_m": 0.059970814104139375,
-          "rotation_deg": 0.61595189426212
-        },
-        {
-          "pair_index": 22,
-          "translation_m": 0.011156452422652521,
-          "rotation_deg": 0.39742394993610364
-        },
-        {
-          "pair_index": 23,
-          "translation_m": 0.04780738274324129,
-          "rotation_deg": 1.7812021332676105
-        },
-        {
-          "pair_index": 24,
-          "translation_m": 0.0580893770008635,
-          "rotation_deg": 0.879332260016813
-        },
-        {
-          "pair_index": 25,
-          "translation_m": 0.12024661823169551,
-          "rotation_deg": 4.3358524167513774
-        },
-        {
-          "pair_index": 26,
-          "translation_m": 0.06196910794842297,
-          "rotation_deg": 1.5238281010443262
-        },
-        {
-          "pair_index": 27,
-          "translation_m": 0.0503874055448458,
-          "rotation_deg": 0.972956387575872
-        },
-        {
-          "pair_index": 28,
-          "translation_m": 0.01757080571201053,
-          "rotation_deg": 0.8111658366205472
-        },
-        {
-          "pair_index": 29,
-          "translation_m": 0.032044188496992296,
-          "rotation_deg": 0.943436351113904
-        },
-        {
-          "pair_index": 30,
-          "translation_m": 0.05418626153418599,
-          "rotation_deg": 0.5111200883804832
-        },
-        {
-          "pair_index": 31,
-          "translation_m": 0.02622969795541729,
-          "rotation_deg": 0.26503765103607685
-        },
-        {
-          "pair_index": 32,
-          "translation_m": 0.10034938173040396,
-          "rotation_deg": 0.8910089412227198
-        },
-        {
-          "pair_index": 33,
-          "translation_m": 0.024232025179701657,
-          "rotation_deg": 0.2983628682948933
-        },
-        {
-          "pair_index": 34,
-          "translation_m": 0.06450981390919311,
-          "rotation_deg": 1.1099995759326005
-        },
-        {
-          "pair_index": 35,
-          "translation_m": 0.06841378002467255,
-          "rotation_deg": 0.765302580707095
-        },
-        {
-          "pair_index": 36,
-          "translation_m": 0.45978165540815585,
-          "rotation_deg": 0.8318777085643659
-        },
-        {
-          "pair_index": 37,
-          "translation_m": 0.31232972397739145,
-          "rotation_deg": 0.7893009066081454
-        },
-        {
-          "pair_index": 38,
-          "translation_m": 0.3910017597095041,
-          "rotation_deg": 0.6583887677988087
-        },
-        {
-          "pair_index": 39,
-          "translation_m": 0.1015358221759577,
-          "rotation_deg": 0.8428062435042994
-        },
-        {
-          "pair_index": 40,
-          "translation_m": 0.1090240114660279,
-          "rotation_deg": 0.8418950507797021
-        },
-        {
-          "pair_index": 41,
-          "translation_m": 0.03539906786781987,
-          "rotation_deg": 0.7658972874383352
-        }
-      ]
-    }
-  },
-  "ground": {
-    "planes": 34,
-    "body_origin_height_above_ground_m": 0.2335,
-    "formula": "d_lidar - (R_X n_lidar)^T t_X - body_height"
-  },
-  "linearized_one_sigma": {
-    "translation_m": [
-      0.007068161359903731,
-      0.007140938677742994,
-      0.00460528013456401
-    ],
-    "rotation_deg": [
-      0.07009913972450056,
-      0.0632417549466229,
-      0.13781143232539678
-    ],
-    "warning": "conditional local estimate; bootstrap is the primary stability check"
-  },
-  "weighted_jacobian_condition_number": 6.8653146384480275,
-  "solver_multistart": {
-    "runs": 12,
-    "candidates_relative_to_best": [
-      {
-        "cost": 165.05915287927994,
-        "success": true,
-        "translation_m": 3.0576433724414325e-08,
-        "rotation_deg": 1.5435010182701515e-07
-      },
-      {
-        "cost": 165.05915287928036,
-        "success": true,
-        "translation_m": 3.132972747129673e-08,
-        "rotation_deg": 1.5835217811052665e-07
-      },
-      {
-        "cost": 165.0591528792959,
-        "success": true,
-        "translation_m": 5.032571008409966e-08,
-        "rotation_deg": 6.019987077228086e-07
-      },
-      {
-        "cost": 165.0591528792966,
-        "success": true,
-        "translation_m": 5.0134365128719625e-08,
-        "rotation_deg": 6.036593761377996e-07
-      },
-      {
-        "cost": 165.059152879271,
-        "success": true,
-        "translation_m": 4.0000992845476256e-09,
-        "rotation_deg": 5.9504483976085874e-08
-      },
-      {
-        "cost": 165.0591528792741,
-        "success": true,
-        "translation_m": 1.71650324878148e-08,
-        "rotation_deg": 2.1433774624387286e-07
-      },
-      {
-        "cost": 165.059152879271,
-        "success": true,
-        "translation_m": 3.8510946546090955e-09,
-        "rotation_deg": 5.7484467409642816e-08
-      },
-      {
-        "cost": 165.05915287927274,
-        "success": true,
-        "translation_m": 1.2609667860271796e-08,
-        "rotation_deg": 1.3972470982253386e-07
-      },
-      {
-        "cost": 165.05915287929693,
-        "success": true,
-        "translation_m": 5.0359957454032455e-08,
-        "rotation_deg": 6.053505895170472e-07
-      },
-      {
-        "cost": 165.05915287927098,
-        "success": true,
-        "translation_m": 0.0,
-        "rotation_deg": 0.0
-      },
-      {
-        "cost": 165.0591528792721,
-        "success": true,
-        "translation_m": 1.123025431013551e-08,
-        "rotation_deg": 3.014422244971439e-08
-      },
-      {
-        "cost": 165.0591528792711,
-        "success": true,
-        "translation_m": 2.4200230224271075e-09,
-        "rotation_deg": 6.741856490734345e-08
-      }
-    ]
-  },
-  "bootstrap": {
-    "runs": 100,
-    "order": [
-      "x_m",
-      "y_m",
-      "z_m",
-      "roll_deg",
-      "pitch_deg",
-      "yaw_deg"
-    ],
-    "std": [
-      0.0030749822448559927,
-      0.0034380377435498433,
-      0.0016315909218529902,
-      0.07586073216888294,
-      0.07187134364073751,
-      0.11146702425116647
-    ],
-    "p025": [
-      1.292007464312339,
-      -0.006797525226093335,
-      0.701848741787294,
-      -0.9789682101604196,
-      1.2351532937224006,
-      -1.211682139162798
-    ],
-    "p975": [
-      1.3029347232892419,
-      0.005407572756192536,
-      0.7084594772174496,
-      -0.705679642362121,
-      1.5258122853862286,
-      -0.8045746213351143
-    ]
-  }
-}
\ No newline at end of file
diff --git a/results/02_data4_calibration/small_gicp/B_estimation.npz b/results/02_data4_calibration/small_gicp/B_estimation.npz
deleted file mode 100644
index db58307..0000000
Binary files a/results/02_data4_calibration/small_gicp/B_estimation.npz and /dev/null differ
diff --git a/results/02_data4_calibration/small_gicp/B_quality.csv b/results/02_data4_calibration/small_gicp/B_quality.csv
deleted file mode 100644
index c3cc963..0000000
--- a/results/02_data4_calibration/small_gicp/B_quality.csv
+++ /dev/null
@@ -1,156 +0,0 @@
-i,j,rtk_translation_m,rtk_rotation_deg,heldout_inlier_ratio,heldout_inlier_rmse_m,hessian_rank,hessian_condition,reverse_translation_m,reverse_rotation_deg,multistart_success_rate,accepted,rejection_reasons
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diff --git a/results/02_data4_calibration/small_gicp/B_quality.json b/results/02_data4_calibration/small_gicp/B_quality.json
deleted file mode 100644
index 7f661a2..0000000
--- a/results/02_data4_calibration/small_gicp/B_quality.json
+++ /dev/null
@@ -1,19969 +0,0 @@
-{
-  "schema_version": 2,
-  "backend": "small_gicp",
-  "transform_convention": "B_ij=T_Li_Lj maps station j points into station i",
-  "raw_point_field": "points_raw",
-  "measured_extrinsic_used_as_initial": false,
-  "stations": 34,
-  "candidate_pairs": 155,
-  "accepted_pairs": 133,
-  "parameters": {
-    "command": "pairs",
-    "backend": "small_gicp",
-    "frames": "<external-data>\\data4_prepared\\frames_all",
-    "body": "<external-data>\\data4_prepared\\body_poses_rear_gga_raw_rear_to_front.csv",
-    "output": "results\\02_data4_calibration\\small_gicp\\B_estimation.npz",
-    "quality_json": "results\\02_data4_calibration\\small_gicp\\B_quality.json",
-    "quality_csv": "results\\02_data4_calibration\\small_gicp\\B_quality.csv",
-    "time_offset": 0.0,
-    "min_stations": 30,
-    "min_pairs": 20,
-    "min_gap": 1,
-    "max_gap": 5,
-    "min_translation": 0.5,
-    "min_rotation": 3.0,
-    "min_range": 2.0,
-    "max_range": 50.0,
-    "z_min": -0.6,
-    "z_max": 5.0,
-    "min_roi_points": 1000,
-    "holdout_fraction": 0.2,
-    "voxels": [
-      0.3,
-      0.15,
-      0.08
-    ],
-    "correspondences": [
-      1.2,
-      0.5,
-      0.25
-    ],
-    "iterations": 60,
-    "threads": 8,
-    "evaluation_distance": 0.25,
-    "min_inlier_ratio": 0.35,
-    "max_inlier_rmse": 0.16,
-    "max_hessian_condition": 100000000.0,
-    "reverse_translation_tolerance": 0.08,
-    "reverse_rotation_tolerance": 0.5,
-    "multistart": 2,
-    "multistart_translation_sigma": 0.3,
-    "multistart_rotation_sigma": 3.0,
-    "multistart_translation_tolerance": 0.08,
-    "multistart_rotation_tolerance": 0.5,
-    "min_multistart_success": 0.5,
-    "seed": 20260721
-  },
-  "accepted_loop_closure": {
-    "count": 204,
-    "translation_rms_m": 0.05535585175309386,
-    "translation_p95_m": 0.1115116379074081,
-    "rotation_rms_deg": 0.7065238289963304,
-    "rotation_p95_deg": 1.3657417416649225
-  },
-  "pairs": [
-    {
-      "i": 0,
-      "j": 1,
-      "lidar_time_i": 1784783825.357129,
-      "lidar_time_j": 1784783905.353819,
-      "frame_counter_i": 382,
-      "frame_counter_j": 1182,
-      "rtk_translation_m": 1.8477087194158957,
-      "rtk_rotation_deg": 24.171297449440786,
-      "nearest_rtk_dt_i_s": 0.0,
-      "nearest_rtk_dt_j_s": 0.0,
-      "initial_B_source": "X0=identity; B0=A (no measured extrinsic)",
-      "B_ij_4x4": [
-        [
-          0.9125981263771286,
-          0.4087746109055665,
-          0.008244829407349786,
-          1.609483991564837
-        ],
-        [
-          -0.4088014793696517,
-          0.9126215324852639,
-          0.0018135350652826935,
-          -1.2615552121092464
-        ],
-        [
-          -0.006783081758140572,
-          -0.005025527161571208,
-          0.9999643663044252,
-          0.007918305352787577
-        ],
-        [
-          0.0,
-          0.0,
-          0.0,
-          1.0
-        ]
-      ],
-      "backend": "small_gicp",
-      "backend_converged": true,
-      "backend_iterations": 3,
-      "backend_num_inliers": 9148,
-      "backend_objective": 925.5850309227212,
-      "backend_elapsed_sec": 0.3304098999942653,
-      "multiscale_stages": [
-        {
-          "voxel_m": 0.3,
-          "max_correspondence_m": 1.2,
-          "converged": true,
-          "iterations": 7,
-          "num_inliers": 4489,
-          "objective": 873.2318068011239
-        },
-        {
-          "voxel_m": 0.15,
-          "max_correspondence_m": 0.5,
-          "converged": true,
-          "iterations": 7,
-          "num_inliers": 7401,
-          "objective": 985.1234245006173
-        },
-        {
-          "voxel_m": 0.08,
-          "max_correspondence_m": 0.25,
-          "converged": true,
-          "iterations": 3,
-          "num_inliers": 9148,
-          "objective": 925.5850309227212
-        }
-      ],
-      "heldout_symmetric": {
-        "evaluated": 7785,
-        "inliers": 6379,
-        "inlier_ratio": 0.8193962748876044,
-        "inlier_rmse_m": 0.11049677170760565,
-        "median_m": 0.10312860156857301,
-        "p90_m": 0.43216665589086356,
-        "p95_m": 0.6431893032606215
-      },
-      "hessian": {
-        "native_order": [
-          "rx_rad",
-          "ry_rad",
-          "rz_rad",
-          "tx_m",
-          "ty_m",
-          "tz_m"
-        ],
-        "scaled_eigenvalues": [
-          59129.030987988175,
-          141835.53829922067,
-          290431.2141896815,
-          487284.4491534459,
-          526614.1106785885,
-          828624.9457322137
-        ],
-        "effective_rank": 6,
-        "scaled_condition_number": 14.01384280930539,
-        "weakest_scaled_direction": [
-          -0.008611429903847459,
-          0.09949068386374309,
-          0.0023060514298579486,
-          -0.46409753819566063,
-          0.8753677187089856,
-          -0.09147109548427051
-        ]
-      },
-      "forward_reverse": {
-        "translation_m": 0.026680306344951596,
-        "rotation_deg": 0.12400141971813113
-      },
-      "multistart": {
-        "runs": 2,
-        "success_rate": 1.0,
-        "deltas": [
-          {
-            "translation_m": 1.5257718890254282e-15,
-            "rotation_deg": 3.066809389089159e-14
-          },
-          {
-            "translation_m": 1.1185402273152979e-15,
-            "rotation_deg": 2.8015561028388492e-14
-          }
-        ]
-      },
-      "accepted": true,
-      "rejection_reasons": []
-    },
-    {
-      "i": 0,
-      "j": 2,
-      "lidar_time_i": 1784783825.357129,
-      "lidar_time_j": 1784783971.0503054,
-      "frame_counter_i": 382,
-      "frame_counter_j": 1839,
-      "rtk_translation_m": 2.633731568575307,
-      "rtk_rotation_deg": 80.09074797031298,
-      "nearest_rtk_dt_i_s": 0.0,
-      "nearest_rtk_dt_j_s": 0.0,
-      "initial_B_source": "X0=identity; B0=A (no measured extrinsic)",
-      "B_ij_4x4": [
-        [
-          0.18426548423554648,
-          0.9828685104373209,
-          -0.003965162060012078,
-          0.12828748804201265
-        ],
-        [
-          -0.9821009084969061,
-          0.1839583434891191,
-          -0.04046150504235337,
-          -3.659471702290386
-        ],
-        [
-          -0.03903891454680426,
-          0.011349848081003564,
-          0.9991732302756845,
-          -0.07048425573871506
-        ],
-        [
-          0.0,
-          0.0,
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-          -0.00467411957355558,
-          0.8193062780796254
-        ]
-      },
-      "forward_reverse": {
-        "translation_m": 0.005559091155811048,
-        "rotation_deg": 0.0330053182501105
-      },
-      "multistart": {
-        "runs": 2,
-        "success_rate": 1.0,
-        "deltas": [
-          {
-            "translation_m": 5.095246377785861e-16,
-            "rotation_deg": 7.369239496130195e-15
-          },
-          {
-            "translation_m": 1.7452973491944015e-15,
-            "rotation_deg": 6.13197128276296e-15
-          }
-        ]
-      },
-      "accepted": true,
-      "rejection_reasons": []
-    },
-    {
-      "i": 32,
-      "j": 33,
-      "lidar_time_i": 1784786396.7558627,
-      "lidar_time_j": 1784786557.4492514,
-      "frame_counter_i": 26097,
-      "frame_counter_j": 27704,
-      "rtk_translation_m": 1.4370687242949811,
-      "rtk_rotation_deg": 91.2822037600631,
-      "nearest_rtk_dt_i_s": 0.0,
-      "nearest_rtk_dt_j_s": 0.0,
-      "initial_B_source": "X0=identity; B0=A (no measured extrinsic)",
-      "B_ij_4x4": [
-        [
-          -0.03553714800116292,
-          0.9993149516431566,
-          -0.010331434284676484,
-          -1.3966905543976256
-        ],
-        [
-          -0.9987095986600396,
-          -0.03588712491476379,
-          -0.03593399239793585,
-          1.6567592534208615
-        ],
-        [
-          -0.0362801413482118,
-          0.009041110981913531,
-          0.9993007603599455,
-          0.18107882372357556
-        ],
-        [
-          0.0,
-          0.0,
-          0.0,
-          1.0
-        ]
-      ],
-      "backend": "small_gicp",
-      "backend_converged": true,
-      "backend_iterations": 18,
-      "backend_num_inliers": 434,
-      "backend_objective": 19.5164628284166,
-      "backend_elapsed_sec": 0.6570993000059389,
-      "multiscale_stages": [
-        {
-          "voxel_m": 0.3,
-          "max_correspondence_m": 1.2,
-          "converged": false,
-          "iterations": 59,
-          "num_inliers": 1049,
-          "objective": 883.1483573831881
-        },
-        {
-          "voxel_m": 0.15,
-          "max_correspondence_m": 0.5,
-          "converged": false,
-          "iterations": 59,
-          "num_inliers": 845,
-          "objective": 182.6938800328335
-        },
-        {
-          "voxel_m": 0.08,
-          "max_correspondence_m": 0.25,
-          "converged": true,
-          "iterations": 18,
-          "num_inliers": 434,
-          "objective": 19.5164628284166
-        }
-      ],
-      "heldout_symmetric": {
-        "evaluated": 8473,
-        "inliers": 368,
-        "inlier_ratio": 0.043432078366576185,
-        "inlier_rmse_m": 0.1661924920133195,
-        "median_m": 1.3116363900492476,
-        "p90_m": 2.516004269498909,
-        "p95_m": 2.6755523843181948
-      },
-      "hessian": {
-        "native_order": [
-          "rx_rad",
-          "ry_rad",
-          "rz_rad",
-          "tx_m",
-          "ty_m",
-          "tz_m"
-        ],
-        "scaled_eigenvalues": [
-          642.7747431708625,
-          954.735320433794,
-          1133.575997940253,
-          1939.7523753118437,
-          14074.629767093451,
-          56882.75167846326
-        ],
-        "effective_rank": 6,
-        "scaled_condition_number": 88.4956235178996,
-        "weakest_scaled_direction": [
-          0.12024798769106836,
-          -0.6749797371841314,
-          0.08183100517680016,
-          -0.05162316535972436,
-          -0.20059941130013623,
-          0.6930666543869539
-        ]
-      },
-      "forward_reverse": {
-        "translation_m": 0.946171384319174,
-        "rotation_deg": 3.5092968853566924
-      },
-      "multistart": {
-        "runs": 2,
-        "success_rate": 0.0,
-        "deltas": [
-          {
-            "translation_m": 2.5266613224139265,
-            "rotation_deg": 1.139524458087656
-          },
-          {
-            "translation_m": 0.8870093669430473,
-            "rotation_deg": 5.456250095042409
-          }
-        ]
-      },
-      "accepted": false,
-      "rejection_reasons": [
-        "heldout_inlier_ratio",
-        "heldout_inlier_rmse",
-        "forward_reverse_translation",
-        "forward_reverse_rotation",
-        "multistart_instability"
-      ]
-    }
-  ]
-}
\ No newline at end of file
diff --git a/results/02_data4_calibration/small_gicp/B_refined.npz b/results/02_data4_calibration/small_gicp/B_refined.npz
deleted file mode 100644
index 5843ea1..0000000
Binary files a/results/02_data4_calibration/small_gicp/B_refined.npz and /dev/null differ
diff --git a/results/02_data4_calibration/small_gicp/B_refined.refinement.json b/results/02_data4_calibration/small_gicp/B_refined.refinement.json
deleted file mode 100644
index 79e3046..0000000
--- a/results/02_data4_calibration/small_gicp/B_refined.refinement.json
+++ /dev/null
@@ -1,1666 +0,0 @@
-{
-  "selection_is_X_independent": true,
-  "criteria": {
-    "min_inlier_ratio": 0.7,
-    "max_inlier_rmse_m": 0.13,
-    "max_rotation_invariant_error_deg": 0.75,
-    "reverse_translation_tolerance_m": 0.05,
-    "reverse_rotation_tolerance_deg": 0.5
-  },
-  "input_pairs": 133,
-  "accepted_pairs": 57,
-  "pairs": [
-    {
-      "i": 0,
-      "j": 1,
-      "heldout_inlier_ratio": 0.8193962748876044,
-      "heldout_inlier_rmse_m": 0.11049677170760565,
-      "rotation_invariant_error_deg": 0.03734008173614711,
-      "reverse_translation_m": 0.026680306344951596,
-      "reverse_rotation_deg": 0.12400141971813113,
-      "accepted": true,
-      "rejection_reasons": []
-    },
-    {
-      "i": 0,
-      "j": 2,
-      "heldout_inlier_ratio": 0.7525388867463684,
-      "heldout_inlier_rmse_m": 0.11492533799497681,
-      "rotation_invariant_error_deg": 0.6760112300786432,
-      "reverse_translation_m": 0.0018465318763874656,
-      "reverse_rotation_deg": 0.03093450642761156,
-      "accepted": true,
-      "rejection_reasons": []
-    },
-    {
-      "i": 0,
-      "j": 3,
-      "heldout_inlier_ratio": 0.628093901505486,
-      "heldout_inlier_rmse_m": 0.12365050970311489,
-      "rotation_invariant_error_deg": 0.3329548009851493,
-      "reverse_translation_m": 0.010524333328229862,
-      "reverse_rotation_deg": 0.23898233567763014,
-      "accepted": false,
-      "rejection_reasons": [
-        "overlap_ratio"
-      ]
-    },
-    {
-      "i": 0,
-      "j": 5,
-      "heldout_inlier_ratio": 0.6015065913370998,
-      "heldout_inlier_rmse_m": 0.12959862169013578,
-      "rotation_invariant_error_deg": 0.8874651368963384,
-      "reverse_translation_m": 0.013711901937629547,
-      "reverse_rotation_deg": 0.26024107991311357,
-      "accepted": false,
-      "rejection_reasons": [
-        "overlap_ratio",
-        "rotation_conjugacy_invariant"
-      ]
-    },
-    {
-      "i": 1,
-      "j": 3,
-      "heldout_inlier_ratio": 0.678820988438572,
-      "heldout_inlier_rmse_m": 0.12109867185657652,
-      "rotation_invariant_error_deg": 0.28201354980991766,
-      "reverse_translation_m": 0.008324315958289934,
-      "reverse_rotation_deg": 0.25689852176843175,
-      "accepted": false,
-      "rejection_reasons": [
-        "overlap_ratio"
-      ]
-    },
-    {
-      "i": 1,
-      "j": 4,
-      "heldout_inlier_ratio": 0.6772473651580905,
-      "heldout_inlier_rmse_m": 0.11157492180388107,
-      "rotation_invariant_error_deg": 0.23808884059471325,
-      "reverse_translation_m": 0.00802452890723869,
-      "reverse_rotation_deg": 0.011334867255723058,
-      "accepted": false,
-      "rejection_reasons": [
-        "overlap_ratio"
-      ]
-    },
-    {
-      "i": 1,
-      "j": 6,
-      "heldout_inlier_ratio": 0.6933789087226231,
-      "heldout_inlier_rmse_m": 0.12162612003144421,
-      "rotation_invariant_error_deg": 0.0750432131524672,
-      "reverse_translation_m": 0.008258211706006158,
-      "reverse_rotation_deg": 0.08942722541817279,
-      "accepted": false,
-      "rejection_reasons": [
-        "overlap_ratio"
-      ]
-    },
-    {
-      "i": 2,
-      "j": 3,
-      "heldout_inlier_ratio": 0.7609663064208518,
-      "heldout_inlier_rmse_m": 0.11583878636897658,
-      "rotation_invariant_error_deg": 0.03805484899682254,
-      "reverse_translation_m": 0.00784220284106163,
-      "reverse_rotation_deg": 0.01711532312869618,
-      "accepted": true,
-      "rejection_reasons": []
-    },
-    {
-      "i": 2,
-      "j": 4,
-      "heldout_inlier_ratio": 0.796748976299789,
-      "heldout_inlier_rmse_m": 0.11484342359047915,
-      "rotation_invariant_error_deg": 0.8619802082203449,
-      "reverse_translation_m": 0.011210942709507262,
-      "reverse_rotation_deg": 0.11462542679280045,
-      "accepted": false,
-      "rejection_reasons": [
-        "rotation_conjugacy_invariant"
-      ]
-    },
-    {
-      "i": 2,
-      "j": 5,
-      "heldout_inlier_ratio": 0.7112112112112112,
-      "heldout_inlier_rmse_m": 0.12001317983504071,
-      "rotation_invariant_error_deg": 0.19305622476466944,
-      "reverse_translation_m": 0.011298647069299764,
-      "reverse_rotation_deg": 0.02158504824207679,
-      "accepted": true,
-      "rejection_reasons": []
-    },
-    {
-      "i": 2,
-      "j": 6,
-      "heldout_inlier_ratio": 0.7254529329785886,
-      "heldout_inlier_rmse_m": 0.11794151013960824,
-      "rotation_invariant_error_deg": 0.5959529359404385,
-      "reverse_translation_m": 0.004729020804343234,
-      "reverse_rotation_deg": 0.026463705119922912,
-      "accepted": true,
-      "rejection_reasons": []
-    },
-    {
-      "i": 2,
-      "j": 7,
-      "heldout_inlier_ratio": 0.7569187603621987,
-      "heldout_inlier_rmse_m": 0.11528530285715083,
-      "rotation_invariant_error_deg": 0.6006463589923925,
-      "reverse_translation_m": 0.011994525026310043,
-      "reverse_rotation_deg": 0.05882394078371607,
-      "accepted": true,
-      "rejection_reasons": []
-    },
-    {
-      "i": 3,
-      "j": 4,
-      "heldout_inlier_ratio": 0.6957378664695738,
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-      "reverse_translation_m": 0.006018969660459514,
-      "reverse_rotation_deg": 0.057234124307389854,
-      "accepted": false,
-      "rejection_reasons": [
-        "overlap_ratio"
-      ]
-    },
-    {
-      "i": 3,
-      "j": 5,
-      "heldout_inlier_ratio": 0.7989069680784996,
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-      "rotation_invariant_error_deg": 0.5566178981223597,
-      "reverse_translation_m": 0.01353229173052898,
-      "reverse_rotation_deg": 0.06486032517688407,
-      "accepted": true,
-      "rejection_reasons": []
-    },
-    {
-      "i": 3,
-      "j": 6,
-      "heldout_inlier_ratio": 0.8435613682092555,
-      "heldout_inlier_rmse_m": 0.11222309863990207,
-      "rotation_invariant_error_deg": 0.24279409865246748,
-      "reverse_translation_m": 0.009512765198853305,
-      "reverse_rotation_deg": 0.09743636874085052,
-      "accepted": true,
-      "rejection_reasons": []
-    },
-    {
-      "i": 3,
-      "j": 7,
-      "heldout_inlier_ratio": 0.8651898734177215,
-      "heldout_inlier_rmse_m": 0.11184568072686094,
-      "rotation_invariant_error_deg": 0.23371684353352862,
-      "reverse_translation_m": 0.010827690226297962,
-      "reverse_rotation_deg": 0.12520280777371934,
-      "accepted": true,
-      "rejection_reasons": []
-    },
-    {
-      "i": 3,
-      "j": 8,
-      "heldout_inlier_ratio": 0.825590155700653,
-      "heldout_inlier_rmse_m": 0.10787987267070262,
-      "rotation_invariant_error_deg": 0.07359256633802147,
-      "reverse_translation_m": 0.0056088079192386986,
-      "reverse_rotation_deg": 0.021536601402145895,
-      "accepted": true,
-      "rejection_reasons": []
-    },
-    {
-      "i": 4,
-      "j": 5,
-      "heldout_inlier_ratio": 0.6652516676773802,
-      "heldout_inlier_rmse_m": 0.12444356767629798,
-      "rotation_invariant_error_deg": 1.0678050691619134,
-      "reverse_translation_m": 0.003155412913416372,
-      "reverse_rotation_deg": 0.05824374716659687,
-      "accepted": false,
-      "rejection_reasons": [
-        "overlap_ratio",
-        "rotation_conjugacy_invariant"
-      ]
-    },
-    {
-      "i": 4,
-      "j": 6,
-      "heldout_inlier_ratio": 0.6551681807021851,
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-      "reverse_translation_m": 0.011212969141455763,
-      "reverse_rotation_deg": 0.08373658947114908,
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-      "rejection_reasons": [
-        "overlap_ratio"
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-    },
-    {
-      "i": 4,
-      "j": 7,
-      "heldout_inlier_ratio": 0.696936001976773,
-      "heldout_inlier_rmse_m": 0.11799538994568655,
-      "rotation_invariant_error_deg": 0.2724963846557813,
-      "reverse_translation_m": 0.00409529177569414,
-      "reverse_rotation_deg": 0.0519770010059835,
-      "accepted": false,
-      "rejection_reasons": [
-        "overlap_ratio"
-      ]
-    },
-    {
-      "i": 4,
-      "j": 8,
-      "heldout_inlier_ratio": 0.7129198332924737,
-      "heldout_inlier_rmse_m": 0.11349036082807595,
-      "rotation_invariant_error_deg": 0.5804550654619618,
-      "reverse_translation_m": 0.01249802665331653,
-      "reverse_rotation_deg": 0.04549823831834878,
-      "accepted": true,
-      "rejection_reasons": []
-    },
-    {
-      "i": 4,
-      "j": 9,
-      "heldout_inlier_ratio": 0.6097234068478128,
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-      "reverse_translation_m": 0.00616984405743089,
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-      "accepted": false,
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-        "overlap_ratio"
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-    },
-    {
-      "i": 5,
-      "j": 6,
-      "heldout_inlier_ratio": 0.7604901596732269,
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-      "reverse_translation_m": 0.01028641250952863,
-      "reverse_rotation_deg": 0.031127073736479716,
-      "accepted": false,
-      "rejection_reasons": [
-        "rotation_conjugacy_invariant"
-      ]
-    },
-    {
-      "i": 5,
-      "j": 7,
-      "heldout_inlier_ratio": 0.8092687180764918,
-      "heldout_inlier_rmse_m": 0.10777871969807898,
-      "rotation_invariant_error_deg": 0.8022146383376452,
-      "reverse_translation_m": 0.010579714886860828,
-      "reverse_rotation_deg": 0.03333492483252218,
-      "accepted": false,
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-    },
-    {
-      "i": 5,
-      "j": 8,
-      "heldout_inlier_ratio": 0.7295760721789643,
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-    },
-    {
-      "i": 5,
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-      "reverse_rotation_deg": 0.17134499262937464,
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-        "heldout_rmse"
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-    },
-    {
-      "i": 6,
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-    {
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-    {
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-        "heldout_rmse"
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-    {
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-    {
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-      "rotation_invariant_error_deg": 0.013598924391089895,
-      "reverse_translation_m": 0.005463604154015333,
-      "reverse_rotation_deg": 0.018583483487870766,
-      "accepted": true,
-      "rejection_reasons": []
-    },
-    {
-      "i": 29,
-      "j": 31,
-      "heldout_inlier_ratio": 0.7254562254562255,
-      "heldout_inlier_rmse_m": 0.11323336570178015,
-      "rotation_invariant_error_deg": 0.5964723771181326,
-      "reverse_translation_m": 0.0050777995851252426,
-      "reverse_rotation_deg": 0.07265894091769333,
-      "accepted": true,
-      "rejection_reasons": []
-    },
-    {
-      "i": 29,
-      "j": 32,
-      "heldout_inlier_ratio": 0.695837657096737,
-      "heldout_inlier_rmse_m": 0.10999820041072961,
-      "rotation_invariant_error_deg": 0.7779150860024799,
-      "reverse_translation_m": 0.011220553177198233,
-      "reverse_rotation_deg": 0.14599088546526143,
-      "accepted": false,
-      "rejection_reasons": [
-        "overlap_ratio",
-        "rotation_conjugacy_invariant"
-      ]
-    },
-    {
-      "i": 29,
-      "j": 33,
-      "heldout_inlier_ratio": 0.6382698298586149,
-      "heldout_inlier_rmse_m": 0.11215583949685817,
-      "rotation_invariant_error_deg": 0.5073524660734563,
-      "reverse_translation_m": 0.018977478007060265,
-      "reverse_rotation_deg": 0.05615608666616428,
-      "accepted": false,
-      "rejection_reasons": [
-        "overlap_ratio"
-      ]
-    },
-    {
-      "i": 30,
-      "j": 31,
-      "heldout_inlier_ratio": 0.8286237272623269,
-      "heldout_inlier_rmse_m": 0.0964659694513182,
-      "rotation_invariant_error_deg": 0.6302983762623384,
-      "reverse_translation_m": 0.018905314487385798,
-      "reverse_rotation_deg": 0.08632503464137033,
-      "accepted": true,
-      "rejection_reasons": []
-    },
-    {
-      "i": 30,
-      "j": 32,
-      "heldout_inlier_ratio": 0.8065326633165829,
-      "heldout_inlier_rmse_m": 0.09815063400019142,
-      "rotation_invariant_error_deg": 0.727984359566662,
-      "reverse_translation_m": 0.007341509941520892,
-      "reverse_rotation_deg": 0.023973741904832375,
-      "accepted": true,
-      "rejection_reasons": []
-    },
-    {
-      "i": 31,
-      "j": 32,
-      "heldout_inlier_ratio": 0.8146841206602162,
-      "heldout_inlier_rmse_m": 0.09914628416022417,
-      "rotation_invariant_error_deg": 0.11733254397336168,
-      "reverse_translation_m": 0.06936877058296162,
-      "reverse_rotation_deg": 0.45703051311645637,
-      "accepted": false,
-      "rejection_reasons": [
-        "forward_reverse_translation"
-      ]
-    },
-    {
-      "i": 31,
-      "j": 33,
-      "heldout_inlier_ratio": 0.7551430598250177,
-      "heldout_inlier_rmse_m": 0.1003246191461096,
-      "rotation_invariant_error_deg": 0.09234543926339711,
-      "reverse_translation_m": 0.005559091155811048,
-      "reverse_rotation_deg": 0.0330053182501105,
-      "accepted": true,
-      "rejection_reasons": []
-    }
-  ]
-}
\ No newline at end of file
diff --git a/results/02_data4_calibration/small_gicp/extrinsic.json b/results/02_data4_calibration/small_gicp/extrinsic.json
deleted file mode 100644
index 058ca0a..0000000
--- a/results/02_data4_calibration/small_gicp/extrinsic.json
+++ /dev/null
@@ -1,489 +0,0 @@
-{
-  "schema_version": 2,
-  "success": true,
-  "message": "`ftol` termination condition is satisfied.",
-  "convention": "T_body_lidar maps raw LiDAR points into rear-axle body frame",
-  "equation": "A_ij X = X B_ij",
-  "measured_extrinsic_used_as_initial": false,
-  "translation_m": [
-    1.2944883843818025,
-    -0.0008838118010001346,
-    0.7058442435591689
-  ],
-  "rotation_rpy_deg_xyz": [
-    -0.7159364624845366,
-    1.3526878670674298,
-    -0.975972089807914
-  ],
-  "quaternion_xyzw": [
-    -0.006146489369094902,
-    0.011856702812467925,
-    -0.008442354678834595,
-    0.999875175166545
-  ],
-  "matrix_4x4": [
-    [
-      0.9995762904917872,
-      0.016736847531056993,
-      0.02381422728959523,
-      1.2944883843818025
-    ],
-    [
-      -0.01702835592221438,
-      0.9997818946318248,
-      0.01209124728823738,
-      -0.0008838118010001346
-    ],
-    [
-      -0.023606663916460907,
-      -0.01249164125009491,
-      0.9996432785337048,
-      0.7058442435591689
-    ],
-    [
-      0.0,
-      0.0,
-      0.0,
-      1.0
-    ]
-  ],
-  "estimation": {
-    "stations": 34,
-    "pairs": 57,
-    "residuals": {
-      "pairs": 57,
-      "translation_m": {
-        "rms": 0.1544348214275169,
-        "median": 0.0705120546692258,
-        "p90": 0.2796247931030114,
-        "p95": 0.38830732511177307,
-        "max": 0.42173620405868173
-      },
-      "rotation_deg": {
-        "rms": 1.6127366820434261,
-        "median": 0.7802394472449041,
-        "p90": 2.0427026963913084,
-        "p95": 4.139878905679253,
-        "max": 4.927876933555878
-      },
-      "per_pair": [
-        {
-          "pair_index": 0,
-          "translation_m": 0.04921586129986855,
-          "rotation_deg": 0.7802394472449041
-        },
-        {
-          "pair_index": 1,
-          "translation_m": 0.06022467069161827,
-          "rotation_deg": 0.8076387678918286
-        },
-        {
-          "pair_index": 2,
-          "translation_m": 0.05733334031955927,
-          "rotation_deg": 0.3801287351167008
-        },
-        {
-          "pair_index": 3,
-          "translation_m": 0.10178704595686662,
-          "rotation_deg": 0.23294290596786388
-        },
-        {
-          "pair_index": 4,
-          "translation_m": 0.0950710667744258,
-          "rotation_deg": 0.8441747973849835
-        },
-        {
-          "pair_index": 5,
-          "translation_m": 0.1482159791451249,
-          "rotation_deg": 0.681326797444399
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-        {
-          "pair_index": 6,
-          "translation_m": 0.02325894326521952,
-          "rotation_deg": 0.6033104606942519
-        },
-        {
-          "pair_index": 7,
-          "translation_m": 0.07474087499522525,
-          "rotation_deg": 0.6507288891948437
-        },
-        {
-          "pair_index": 8,
-          "translation_m": 0.18825515016508942,
-          "rotation_deg": 0.26486292076967255
-        },
-        {
-          "pair_index": 9,
-          "translation_m": 0.04309283328904936,
-          "rotation_deg": 0.13788972833567684
-        },
-        {
-          "pair_index": 10,
-          "translation_m": 0.04634466299044426,
-          "rotation_deg": 0.727856852897771
-        },
-        {
-          "pair_index": 11,
-          "translation_m": 0.043890799917503956,
-          "rotation_deg": 0.7033085139548623
-        },
-        {
-          "pair_index": 12,
-          "translation_m": 0.06569153273548976,
-          "rotation_deg": 0.8215251942968772
-        },
-        {
-          "pair_index": 13,
-          "translation_m": 0.05085505830053342,
-          "rotation_deg": 0.5703942163369722
-        },
-        {
-          "pair_index": 14,
-          "translation_m": 0.08080041374696341,
-          "rotation_deg": 0.7042489825699358
-        },
-        {
-          "pair_index": 15,
-          "translation_m": 0.028283768727744116,
-          "rotation_deg": 0.5815552521395532
-        },
-        {
-          "pair_index": 16,
-          "translation_m": 0.034152028863445455,
-          "rotation_deg": 1.0076363281960339
-        },
-        {
-          "pair_index": 17,
-          "translation_m": 0.10661935094245772,
-          "rotation_deg": 0.585736616100307
-        },
-        {
-          "pair_index": 18,
-          "translation_m": 0.0705120546692258,
-          "rotation_deg": 0.8052707169746115
-        },
-        {
-          "pair_index": 19,
-          "translation_m": 0.06442322486081886,
-          "rotation_deg": 2.1113003980243557
-        },
-        {
-          "pair_index": 20,
-          "translation_m": 0.058531034305082885,
-          "rotation_deg": 0.5873890947329841
-        },
-        {
-          "pair_index": 21,
-          "translation_m": 0.06915436202628812,
-          "rotation_deg": 0.4455496836075116
-        },
-        {
-          "pair_index": 22,
-          "translation_m": 0.1484005911609239,
-          "rotation_deg": 1.9969708953026104
-        },
-        {
-          "pair_index": 23,
-          "translation_m": 0.10429385187976488,
-          "rotation_deg": 0.12781289285231975
-        },
-        {
-          "pair_index": 24,
-          "translation_m": 0.06859842051942554,
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-        {
-          "pair_index": 25,
-          "translation_m": 0.037990236699121674,
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-        {
-          "pair_index": 26,
-          "translation_m": 0.03189885614531801,
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-        {
-          "pair_index": 27,
-          "translation_m": 0.07672961622319935,
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-        },
-        {
-          "pair_index": 28,
-          "translation_m": 0.069983101896218,
-          "rotation_deg": 0.4729689795147634
-        },
-        {
-          "pair_index": 29,
-          "translation_m": 0.016135065100391668,
-          "rotation_deg": 0.3789407761818106
-        },
-        {
-          "pair_index": 30,
-          "translation_m": 0.07432095926140471,
-          "rotation_deg": 1.8120862981058055
-        },
-        {
-          "pair_index": 31,
-          "translation_m": 0.17890921343127023,
-          "rotation_deg": 3.97184190714068
-        },
-        {
-          "pair_index": 32,
-          "translation_m": 0.2459042707502872,
-          "rotation_deg": 4.617881335971262
-        },
-        {
-          "pair_index": 33,
-          "translation_m": 0.06334407979243162,
-          "rotation_deg": 0.8238155509065317
-        },
-        {
-          "pair_index": 34,
-          "translation_m": 0.07743513463604834,
-          "rotation_deg": 4.0203782981062535
-        },
-        {
-          "pair_index": 35,
-          "translation_m": 0.15971289980951447,
-          "rotation_deg": 4.84466491195667
-        },
-        {
-          "pair_index": 36,
-          "translation_m": 0.13395086756218255,
-          "rotation_deg": 4.927876933555878
-        },
-        {
-          "pair_index": 37,
-          "translation_m": 0.06599998782040693,
-          "rotation_deg": 1.9960824610834838
-        },
-        {
-          "pair_index": 38,
-          "translation_m": 0.04503412561992633,
-          "rotation_deg": 1.279332716204477
-        },
-        {
-          "pair_index": 39,
-          "translation_m": 0.11215573119400024,
-          "rotation_deg": 0.5578231171630792
-        },
-        {
-          "pair_index": 40,
-          "translation_m": 0.05509905448014895,
-          "rotation_deg": 0.6608982729619334
-        },
-        {
-          "pair_index": 41,
-          "translation_m": 0.007272665876828039,
-          "rotation_deg": 1.2124341117031159
-        },
-        {
-          "pair_index": 42,
-          "translation_m": 0.055811383114362484,
-          "rotation_deg": 0.8153248357421402
-        },
-        {
-          "pair_index": 43,
-          "translation_m": 0.03138324591270751,
-          "rotation_deg": 1.2136591021205085
-        },
-        {
-          "pair_index": 44,
-          "translation_m": 0.13982233632280833,
-          "rotation_deg": 1.2089791291543672
-        },
-        {
-          "pair_index": 45,
-          "translation_m": 0.42173620405868173,
-          "rotation_deg": 1.126390973143559
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-        {
-          "pair_index": 46,
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-        {
-          "pair_index": 47,
-          "translation_m": 0.08146548874814821,
-          "rotation_deg": 1.5984131745791201
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-        {
-          "pair_index": 48,
-          "translation_m": 0.40597723810744263,
-          "rotation_deg": 1.3479854285502366
-        },
-        {
-          "pair_index": 49,
-          "translation_m": 0.3864154920341234,
-          "rotation_deg": 0.6215042157245596
-        },
-        {
-          "pair_index": 50,
-          "translation_m": 0.18945577362130134,
-          "rotation_deg": 0.596177211598774
-        },
-        {
-          "pair_index": 51,
-          "translation_m": 0.37813335218979344,
-          "rotation_deg": 1.0668602650100487
-        },
-        {
-          "pair_index": 52,
-          "translation_m": 0.330205576632098,
-          "rotation_deg": 0.40979383494055255
-        },
-        {
-          "pair_index": 53,
-          "translation_m": 0.39587465742237204,
-          "rotation_deg": 0.7934150366951904
-        },
-        {
-          "pair_index": 54,
-          "translation_m": 0.060998991546499626,
-          "rotation_deg": 0.9224390837063629
-        },
-        {
-          "pair_index": 55,
-          "translation_m": 0.0952510183208545,
-          "rotation_deg": 0.8616718556937568
-        },
-        {
-          "pair_index": 56,
-          "translation_m": 0.10976329201195999,
-          "rotation_deg": 0.5415573303416338
-        }
-      ]
-    }
-  },
-  "ground": {
-    "planes": 34,
-    "body_origin_height_above_ground_m": 0.2335,
-    "formula": "d_lidar - (R_X n_lidar)^T t_X - body_height"
-  },
-  "linearized_one_sigma": {
-    "translation_m": [
-      0.006072210871275005,
-      0.0060852661675311025,
-      0.005465720025368553
-    ],
-    "rotation_deg": [
-      0.06255688904352227,
-      0.06213349734715941,
-      0.13055508827073753
-    ],
-    "warning": "conditional local estimate; bootstrap is the primary stability check"
-  },
-  "weighted_jacobian_condition_number": 6.040138286165465,
-  "solver_multistart": {
-    "runs": 12,
-    "candidates_relative_to_best": [
-      {
-        "cost": 324.2098227991519,
-        "success": true,
-        "translation_m": 5.570266299009551e-09,
-        "rotation_deg": 1.4455049406405054e-07
-      },
-      {
-        "cost": 324.20982279914983,
-        "success": true,
-        "translation_m": 0.0,
-        "rotation_deg": 0.0
-      },
-      {
-        "cost": 324.20982279915165,
-        "success": true,
-        "translation_m": 5.216823166795417e-09,
-        "rotation_deg": 1.973338877475283e-07
-      },
-      {
-        "cost": 324.20982279915034,
-        "success": true,
-        "translation_m": 1.3901066622882166e-09,
-        "rotation_deg": 6.335210062786435e-08
-      },
-      {
-        "cost": 324.20982279914995,
-        "success": true,
-        "translation_m": 3.578733410578741e-10,
-        "rotation_deg": 6.852733510041159e-09
-      },
-      {
-        "cost": 324.20982279914983,
-        "success": true,
-        "translation_m": 6.594966941115627e-10,
-        "rotation_deg": 2.2216701960527812e-08
-      },
-      {
-        "cost": 324.20982279914983,
-        "success": true,
-        "translation_m": 2.1650538139486925e-09,
-        "rotation_deg": 3.6255288379996055e-08
-      },
-      {
-        "cost": 324.2098227991501,
-        "success": true,
-        "translation_m": 1.5027981325208515e-09,
-        "rotation_deg": 6.326578543393082e-08
-      },
-      {
-        "cost": 324.20982279914983,
-        "success": true,
-        "translation_m": 6.094320168262204e-10,
-        "rotation_deg": 1.025130160040861e-08
-      },
-      {
-        "cost": 324.2098227991552,
-        "success": true,
-        "translation_m": 1.057266183614633e-08,
-        "rotation_deg": 3.643863231629731e-07
-      },
-      {
-        "cost": 324.20982279915063,
-        "success": true,
-        "translation_m": 3.9489601150102006e-09,
-        "rotation_deg": 1.359274031832874e-07
-      },
-      {
-        "cost": 324.20982279914983,
-        "success": true,
-        "translation_m": 6.276644321676319e-10,
-        "rotation_deg": 2.14493230752589e-08
-      }
-    ]
-  },
-  "bootstrap": {
-    "runs": 100,
-    "order": [
-      "x_m",
-      "y_m",
-      "z_m",
-      "roll_deg",
-      "pitch_deg",
-      "yaw_deg"
-    ],
-    "std": [
-      0.003048001100427371,
-      0.0025869752895426976,
-      0.0014870952541001317,
-      0.09174691854497609,
-      0.06502786700039134,
-      0.11777557058586356
-    ],
-    "p025": [
-      1.2892012505330883,
-      -0.0051467048024525786,
-      0.7035478241042927,
-      -0.8634755073850175,
-      1.2139289883714506,
-      -1.173046710195043
-    ],
-    "p975": [
-      1.2997598841406142,
-      0.005003259375615847,
-      0.7090711194920217,
-      -0.48035430043405547,
-      1.4534667429791082,
-      -0.7593758945747364
-    ]
-  }
-}
\ No newline at end of file
diff --git a/results/03_comparison/README.md b/results/03_comparison/README.md
deleted file mode 100644
index 37f92f4..0000000
--- a/results/03_comparison/README.md
+++ /dev/null
@@ -1,7 +0,0 @@
-# 跨批比较
-
-- `extrinsic_difference.json`：data4 X 相对历史部署 X 的严格 SE(3) 差，约 `1.592 cm / 0.234°`。
-- `old_extrinsic_on_data4.json`：历史部署 X 在 data4 B 上的残差，约 `0.11953 m / 1.24836°`。
-- `data4_extrinsic_on_previous_batch2.json`：data4 X 在历史第二批 B 上的残差，约 `0.07931 m / 0.98926°`。
-
-两套 X 的跨批表现接近，而 data4 自身估计残差更高；因此维持历史部署值，data4 只作为候选。
diff --git a/results/03_comparison/data4_extrinsic_on_previous_batch2.json b/results/03_comparison/data4_extrinsic_on_previous_batch2.json
deleted file mode 100644
index adacde3..0000000
--- a/results/03_comparison/data4_extrinsic_on_previous_batch2.json
+++ /dev/null
@@ -1,298 +0,0 @@
-{
-  "role": "auxiliary check only; first-batch RTK is sparse",
-  "blind_with_respect_to_X": true,
-  "note": "No AX residual was used to select these pairs",
-  "stations": 38,
-  "metrics": {
-    "pairs": 39,
-    "translation_m": {
-      "rms": 0.07931219315845621,
-      "median": 0.0521831021438143,
-      "p90": 0.1205091988381832,
-      "p95": 0.14405284012014574,
-      "max": 0.23166749945892554
-    },
-    "rotation_deg": {
-      "rms": 0.9892579681085032,
-      "median": 0.8987168885592437,
-      "p90": 1.5241504377222574,
-      "p95": 1.5453098245907155,
-      "max": 1.8288069823538258
-    },
-    "per_pair": [
-      {
-        "pair_index": 0,
-        "translation_m": 0.13184857122951013,
-        "rotation_deg": 0.4578882478759752,
-        "i": 0,
-        "j": 2
-      },
-      {
-        "pair_index": 1,
-        "translation_m": 0.11088249231082419,
-        "rotation_deg": 0.49123829458862667,
-        "i": 0,
-        "j": 3
-      },
-      {
-        "pair_index": 2,
-        "translation_m": 0.06122066543511726,
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-      {
-        "pair_index": 3,
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-        "rotation_deg": 0.6513155675962176,
-        "i": 1,
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-      {
-        "pair_index": 4,
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-        "rotation_deg": 0.3726639533978929,
-        "i": 2,
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-      {
-        "pair_index": 5,
-        "translation_m": 0.07839704351948763,
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-      },
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-        "pair_index": 6,
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-        "rotation_deg": 0.8674541404693262,
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-      {
-        "pair_index": 7,
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-        "j": 5
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-      {
-        "pair_index": 8,
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-        "pair_index": 10,
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-      {
-        "pair_index": 11,
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-      {
-        "pair_index": 12,
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-      {
-        "pair_index": 13,
-        "translation_m": 0.05534374617362978,
-        "rotation_deg": 0.9177398533680782,
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-      },
-      {
-        "pair_index": 14,
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-        "rotation_deg": 1.8288069823538258,
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-      {
-        "pair_index": 15,
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-        "j": 15
-      },
-      {
-        "pair_index": 16,
-        "translation_m": 0.20909038047616038,
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-        "j": 16
-      },
-      {
-        "pair_index": 17,
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-        "pair_index": 18,
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-        "j": 19
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-      {
-        "pair_index": 20,
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-      {
-        "pair_index": 21,
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-        "j": 24
-      },
-      {
-        "pair_index": 22,
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-        "j": 25
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-      {
-        "pair_index": 23,
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-        "pair_index": 24,
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-        "j": 25
-      },
-      {
-        "pair_index": 25,
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-        "j": 26
-      },
-      {
-        "pair_index": 26,
-        "translation_m": 0.08267778191372169,
-        "rotation_deg": 0.9059437837656906,
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-        "j": 27
-      },
-      {
-        "pair_index": 27,
-        "translation_m": 0.038589920757972004,
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-        "j": 27
-      },
-      {
-        "pair_index": 28,
-        "translation_m": 0.05488335734683258,
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-        "j": 28
-      },
-      {
-        "pair_index": 29,
-        "translation_m": 0.022562161090077113,
-        "rotation_deg": 1.5336717731182645,
-        "i": 26,
-        "j": 29
-      },
-      {
-        "pair_index": 30,
-        "translation_m": 0.016794927865731942,
-        "rotation_deg": 1.4945757001638067,
-        "i": 27,
-        "j": 30
-      },
-      {
-        "pair_index": 31,
-        "translation_m": 0.08618762377782405,
-        "rotation_deg": 1.5364181917868804,
-        "i": 30,
-        "j": 31
-      },
-      {
-        "pair_index": 32,
-        "translation_m": 0.06980420384374487,
-        "rotation_deg": 0.7086752430201493,
-        "i": 30,
-        "j": 32
-      },
-      {
-        "pair_index": 33,
-        "translation_m": 0.032647030192474995,
-        "rotation_deg": 1.2921319816631744,
-        "i": 32,
-        "j": 33
-      },
-      {
-        "pair_index": 34,
-        "translation_m": 0.0345860258877476,
-        "rotation_deg": 1.374123371412574,
-        "i": 32,
-        "j": 34
-      },
-      {
-        "pair_index": 35,
-        "translation_m": 0.05213790087077668,
-        "rotation_deg": 0.46701073818826994,
-        "i": 32,
-        "j": 35
-      },
-      {
-        "pair_index": 36,
-        "translation_m": 0.023288081661695596,
-        "rotation_deg": 0.15454273191995999,
-        "i": 33,
-        "j": 34
-      },
-      {
-        "pair_index": 37,
-        "translation_m": 0.035256268159629366,
-        "rotation_deg": 0.9445397555422734,
-        "i": 33,
-        "j": 35
-      },
-      {
-        "pair_index": 38,
-        "translation_m": 0.020736197670988343,
-        "rotation_deg": 1.137619185440334,
-        "i": 35,
-        "j": 36
-      }
-    ]
-  }
-}
\ No newline at end of file
diff --git a/results/03_comparison/extrinsic_difference.json b/results/03_comparison/extrinsic_difference.json
deleted file mode 100644
index 5642112..0000000
--- a/results/03_comparison/extrinsic_difference.json
+++ /dev/null
@@ -1,43 +0,0 @@
-{
-  "convention": "delta = inverse(reference) @ candidate",
-  "reference": "results\\01_previous_two_batches\\final_extrinsic_deployment.json",
-  "candidate": "results\\02_data4_calibration\\consensus\\extrinsic.json",
-  "candidate_minus_reference_translation_xyz_m": [
-    0.002616328047628791,
-    -0.0016393602019739468,
-    -0.01562078923962118
-  ],
-  "candidate_minus_reference_rpy_xyz_deg": [
-    -0.006740470942029009,
-    0.1911623881626312,
-    -0.13523257777677677
-  ],
-  "relative_translation_norm_m": 0.01592299377608647,
-  "relative_rotation_deg": 0.23416878770707064,
-  "relative_matrix_4x4": [
-    [
-      0.9999916502190469,
-      0.0023133957658166954,
-      0.003368633583168801,
-      0.0029672356800607425
-    ],
-    [
-      -0.0023136119190219507,
-      0.9999973217800623,
-      6.027097638170339e-05,
-      -0.0013876386622047616
-    ],
-    [
-      -0.0033684851306055737,
-      -6.80641839411564e-05,
-      0.999994324321489,
-      -0.015582416441470737
-    ],
-    [
-      0.0,
-      0.0,
-      0.0,
-      1.0
-    ]
-  ]
-}
\ No newline at end of file
diff --git a/results/03_comparison/old_extrinsic_on_data4.json b/results/03_comparison/old_extrinsic_on_data4.json
deleted file mode 100644
index bfe83ca..0000000
--- a/results/03_comparison/old_extrinsic_on_data4.json
+++ /dev/null
@@ -1,207 +0,0 @@
-{
-  "role": "auxiliary check only; first-batch RTK is sparse",
-  "blind_with_respect_to_X": true,
-  "note": "No AX residual was used to select these pairs",
-  "stations": 34,
-  "metrics": {
-    "pairs": 26,
-    "translation_m": {
-      "rms": 0.11953342461680516,
-      "median": 0.059870553274397435,
-      "p90": 0.11852081980116268,
-      "p95": 0.27001896145006843,
-      "max": 0.3924432090639719
-    },
-    "rotation_deg": {
-      "rms": 1.248363434126574,
-      "median": 0.7472573318442859,
-      "p90": 1.7836452528035456,
-      "p95": 2.0119235382379705,
-      "max": 4.302962170390954
-    },
-    "per_pair": [
-      {
-        "pair_index": 0,
-        "translation_m": 0.05017939301544147,
-        "rotation_deg": 0.7621142667147064,
-        "i": 0,
-        "j": 2
-      },
-      {
-        "pair_index": 1,
-        "translation_m": 0.05476119605552225,
-        "rotation_deg": 0.39488243852657817,
-        "i": 2,
-        "j": 3
-      },
-      {
-        "pair_index": 2,
-        "translation_m": 0.11117501211320562,
-        "rotation_deg": 0.29330702638456563,
-        "i": 2,
-        "j": 5
-      },
-      {
-        "pair_index": 3,
-        "translation_m": 0.06643052326439366,
-        "rotation_deg": 0.5530967273631149,
-        "i": 3,
-        "j": 5
-      },
-      {
-        "pair_index": 4,
-        "translation_m": 0.028182994383263396,
-        "rotation_deg": 0.5499639343413396,
-        "i": 5,
-        "j": 8
-      },
-      {
-        "pair_index": 5,
-        "translation_m": 0.06086463130525318,
-        "rotation_deg": 0.6985420749542534,
-        "i": 6,
-        "j": 7
-      },
-      {
-        "pair_index": 6,
-        "translation_m": 0.020630277131513722,
-        "rotation_deg": 0.6820744752666614,
-        "i": 6,
-        "j": 8
-      },
-      {
-        "pair_index": 7,
-        "translation_m": 0.046848360772821,
-        "rotation_deg": 0.8723393366986318,
-        "i": 12,
-        "j": 14
-      },
-      {
-        "pair_index": 8,
-        "translation_m": 0.05887647524354169,
-        "rotation_deg": 1.9071782288631753,
-        "i": 13,
-        "j": 16
-      },
-      {
-        "pair_index": 9,
-        "translation_m": 0.11661768017132504,
-        "rotation_deg": 2.046838641362902,
-        "i": 15,
-        "j": 16
-      },
-      {
-        "pair_index": 10,
-        "translation_m": 0.06473893802255462,
-        "rotation_deg": 0.30644679433866145,
-        "i": 15,
-        "j": 17
-      },
-      {
-        "pair_index": 11,
-        "translation_m": 0.04963073408543951,
-        "rotation_deg": 0.33998803648541337,
-        "i": 15,
-        "j": 18
-      },
-      {
-        "pair_index": 12,
-        "translation_m": 0.03313618555659487,
-        "rotation_deg": 0.5283154781000993,
-        "i": 16,
-        "j": 19
-      },
-      {
-        "pair_index": 13,
-        "translation_m": 0.0691797699772094,
-        "rotation_deg": 0.6320358674350408,
-        "i": 21,
-        "j": 22
-      },
-      {
-        "pair_index": 14,
-        "translation_m": 0.042364105706927925,
-        "rotation_deg": 1.660112276743916,
-        "i": 21,
-        "j": 24
-      },
-      {
-        "pair_index": 15,
-        "translation_m": 0.07073443988383908,
-        "rotation_deg": 0.8343384286314613,
-        "i": 22,
-        "j": 23
-      },
-      {
-        "pair_index": 16,
-        "translation_m": 0.12042395943100032,
-        "rotation_deg": 4.302962170390954,
-        "i": 22,
-        "j": 25
-      },
-      {
-        "pair_index": 17,
-        "translation_m": 0.05181438442870987,
-        "rotation_deg": 0.8455629957527,
-        "i": 25,
-        "j": 26
-      },
-      {
-        "pair_index": 18,
-        "translation_m": 0.032857670083788,
-        "rotation_deg": 0.7324003969738653,
-        "i": 25,
-        "j": 28
-      },
-      {
-        "pair_index": 19,
-        "translation_m": 0.05285636518357229,
-        "rotation_deg": 0.4369186254063126,
-        "i": 26,
-        "j": 27
-      },
-      {
-        "pair_index": 20,
-        "translation_m": 0.10251045240958172,
-        "rotation_deg": 1.0529040723274141,
-        "i": 26,
-        "j": 29
-      },
-      {
-        "pair_index": 21,
-        "translation_m": 0.023054151271876995,
-        "rotation_deg": 0.24976946582216739,
-        "i": 27,
-        "j": 28
-      },
-      {
-        "pair_index": 22,
-        "translation_m": 0.06593100197822659,
-        "rotation_deg": 1.2515362824917693,
-        "i": 27,
-        "j": 29
-      },
-      {
-        "pair_index": 23,
-        "translation_m": 0.31988396212309117,
-        "rotation_deg": 1.0256849788735003,
-        "i": 29,
-        "j": 30
-      },
-      {
-        "pair_index": 24,
-        "translation_m": 0.3924432090639719,
-        "rotation_deg": 0.8042671494244682,
-        "i": 29,
-        "j": 31
-      },
-      {
-        "pair_index": 25,
-        "translation_m": 0.11357259403662164,
-        "rotation_deg": 0.901297615800165,
-        "i": 30,
-        "j": 32
-      }
-    ]
-  }
-}
\ No newline at end of file
diff --git a/results/README.md b/results/README.md
index 5676a2e..e43ace6 100644
--- a/results/README.md
+++ b/results/README.md
@@ -1,21 +1,5 @@
-# 结果目录
+# results目录
 
-本目录只归档轻量标定产物，不包含原始 dlog、rscap、逐帧 NPZ 或完整点云。
+`reference_data4/`是本仓库附带的精简参考结果。新的运行结果应写到仓库外目录或`outputs/`，不要覆盖参考结果。
 
-| 目录 | 内容 | 使用建议 |
-|---|---|---|
-| `01_previous_two_batches/` | 第二批求解、第一批辅助复核的历史部署结果；含 Open3D、small_gicp、consensus B、质量和灵敏度文件 | 当前部署基线 |
-| `02_data4_calibration/` | data4 的 Open3D、small_gicp、consensus B 和独立 X | 候选/稳定性证据 |
-| `03_comparison/` | 两套 X 的 SE(3) 差以及互换批次后的 AX 残差 | 跨批判断依据 |
-
-最终部署文件是 `01_previous_two_batches/final_extrinsic_deployment.json`。`02_data4_calibration/final_extrinsic_data4.json` 不应在没有新增独立证据时覆盖它。
-
-常见文件：
-
-- `B_*_estimation.npz`：后端原始运动对 B。
-- `B_*_quality.json/csv`：配准和 Hessian/信息矩阵质量。
-- `B_*_refined.npz`：X 无关筛选后的 B。
-- `B_*_consensus.npz` 或 `consensus/B_consensus.npz`：双后端认可的 B。
-- `extrinsic*.json`：由对应 B 和地面约束求出的 X。
-- `*_check.json`：把给定 X 应用于另一批 B 的残差，不是重新求 X。
-- `ground_planes*.csv`：每站地面平面参数。
+参考结果保留最终矩阵、共识B、两后端精筛B、逐对CSV/筛选审计和地面平面；未保留原始点云、逐帧combined数据、冗长的初筛JSON和带本机绝对路径的过程文件。
diff --git a/LiDAR_RTK_Direct_Calibration/results/reference_data4/README.md b/results/reference_data4/README.md
similarity index 100%
rename from LiDAR_RTK_Direct_Calibration/results/reference_data4/README.md
rename to results/reference_data4/README.md
diff --git a/LiDAR_RTK_Direct_Calibration/results/reference_data4/common/ground_planes.csv b/results/reference_data4/common/ground_planes.csv
similarity index 100%
rename from LiDAR_RTK_Direct_Calibration/results/reference_data4/common/ground_planes.csv
rename to results/reference_data4/common/ground_planes.csv
diff --git a/LiDAR_RTK_Direct_Calibration/results/reference_data4/consensus/B_consensus.consensus.json b/results/reference_data4/consensus/B_consensus.consensus.json
similarity index 100%
rename from LiDAR_RTK_Direct_Calibration/results/reference_data4/consensus/B_consensus.consensus.json
rename to results/reference_data4/consensus/B_consensus.consensus.json
diff --git a/LiDAR_RTK_Direct_Calibration/results/reference_data4/consensus/B_consensus.npz b/results/reference_data4/consensus/B_consensus.npz
similarity index 100%
rename from LiDAR_RTK_Direct_Calibration/results/reference_data4/consensus/B_consensus.npz
rename to results/reference_data4/consensus/B_consensus.npz
diff --git a/LiDAR_RTK_Direct_Calibration/results/reference_data4/consensus/extrinsic_rtk_lidar.json b/results/reference_data4/consensus/extrinsic_rtk_lidar.json
similarity index 100%
rename from LiDAR_RTK_Direct_Calibration/results/reference_data4/consensus/extrinsic_rtk_lidar.json
rename to results/reference_data4/consensus/extrinsic_rtk_lidar.json
diff --git a/LiDAR_RTK_Direct_Calibration/results/reference_data4/final_T_RTK_lidar.json b/results/reference_data4/final_T_RTK_lidar.json
similarity index 100%
rename from LiDAR_RTK_Direct_Calibration/results/reference_data4/final_T_RTK_lidar.json
rename to results/reference_data4/final_T_RTK_lidar.json
diff --git a/LiDAR_RTK_Direct_Calibration/results/reference_data4/open3d_gicp/B_quality.csv b/results/reference_data4/open3d_gicp/B_quality.csv
similarity index 100%
rename from LiDAR_RTK_Direct_Calibration/results/reference_data4/open3d_gicp/B_quality.csv
rename to results/reference_data4/open3d_gicp/B_quality.csv
diff --git a/LiDAR_RTK_Direct_Calibration/results/reference_data4/open3d_gicp/B_refined.npz b/results/reference_data4/open3d_gicp/B_refined.npz
similarity index 100%
rename from LiDAR_RTK_Direct_Calibration/results/reference_data4/open3d_gicp/B_refined.npz
rename to results/reference_data4/open3d_gicp/B_refined.npz
diff --git a/LiDAR_RTK_Direct_Calibration/results/reference_data4/open3d_gicp/B_refined.refinement.json b/results/reference_data4/open3d_gicp/B_refined.refinement.json
similarity index 100%
rename from LiDAR_RTK_Direct_Calibration/results/reference_data4/open3d_gicp/B_refined.refinement.json
rename to results/reference_data4/open3d_gicp/B_refined.refinement.json
diff --git a/LiDAR_RTK_Direct_Calibration/results/reference_data4/open3d_gicp/extrinsic_rtk_lidar.json b/results/reference_data4/open3d_gicp/extrinsic_rtk_lidar.json
similarity index 100%
rename from LiDAR_RTK_Direct_Calibration/results/reference_data4/open3d_gicp/extrinsic_rtk_lidar.json
rename to results/reference_data4/open3d_gicp/extrinsic_rtk_lidar.json
diff --git a/LiDAR_RTK_Direct_Calibration/results/reference_data4/small_gicp/B_quality.csv b/results/reference_data4/small_gicp/B_quality.csv
similarity index 100%
rename from LiDAR_RTK_Direct_Calibration/results/reference_data4/small_gicp/B_quality.csv
rename to results/reference_data4/small_gicp/B_quality.csv
diff --git a/LiDAR_RTK_Direct_Calibration/results/reference_data4/small_gicp/B_refined.npz b/results/reference_data4/small_gicp/B_refined.npz
similarity index 100%
rename from LiDAR_RTK_Direct_Calibration/results/reference_data4/small_gicp/B_refined.npz
rename to results/reference_data4/small_gicp/B_refined.npz
diff --git a/LiDAR_RTK_Direct_Calibration/results/reference_data4/small_gicp/B_refined.refinement.json b/results/reference_data4/small_gicp/B_refined.refinement.json
similarity index 100%
rename from LiDAR_RTK_Direct_Calibration/results/reference_data4/small_gicp/B_refined.refinement.json
rename to results/reference_data4/small_gicp/B_refined.refinement.json
diff --git a/LiDAR_RTK_Direct_Calibration/results/reference_data4/small_gicp/extrinsic_rtk_lidar.json b/results/reference_data4/small_gicp/extrinsic_rtk_lidar.json
similarity index 100%
rename from LiDAR_RTK_Direct_Calibration/results/reference_data4/small_gicp/extrinsic_rtk_lidar.json
rename to results/reference_data4/small_gicp/extrinsic_rtk_lidar.json
diff --git a/LiDAR_RTK_Direct_Calibration/results/reference_data4/summary.json b/results/reference_data4/summary.json
similarity index 100%
rename from LiDAR_RTK_Direct_Calibration/results/reference_data4/summary.json
rename to results/reference_data4/summary.json
diff --git a/run/README.md b/run/README.md
index 4839b69..120bf1c 100644
--- a/run/README.md
+++ b/run/README.md
@@ -1,27 +1,14 @@
-# run
+# run目录
 
-本目录是 PowerShell 运行入口；完整流程、参数解释、验收方法和代码职责统一见仓库根目录 `README.md`。
+根README包含完整复现命令；这里仅列入口职责。
 
-| 脚本 | 使用时机 |
+| 脚本 | 用途 |
 |---|---|
-| `export_legacy_stations.ps1` | 第一、第二批式逐站 dlog 导出。 |
-| `export_multisensor_stations.ps1` | LiDAR dlog + 独立 RTK/IMU rscap 导出和时间关联。 |
-| `prepare_legacy_dataset.ps1` | 旧式导出结果生成 prepared。 |
-| `prepare_multisensor_dataset.ps1` | 多传感器 combined 结果生成 prepared。 |
-| `run_single_dataset.ps1` | 单批数据运行 small_gicp、Open3D、consensus 和 X 求解。 |
-| `run_all.ps1` | 第二批求解、第一批辅助复核的历史流程。 |
-| `run_consensus_finish.ps1` | 从已有两个后端 B 重做 consensus。 |
-| `run_sensitivity_scan.ps1` | 指定 Pair 的外参角度灵敏度扫描。 |
-| `view_result.ps1` | 传入 frames、B、X 查看 3D 配准及增量。 |
+| `run_full_pipeline.ps1` | 从逐站LiDAR dlog、RTK rscap、IMU rscap一直运行到最终`T_RTK_lidar` |
+| `export_multisensor_stations.ps1` | 解析原始三传感器数据并按LiDAR帧生成combined NPZ |
+| `prepare_multisensor_dataset.ps1` | 每站选一帧，生成yaw-only RTK参考轨迹和`frames_all` |
+| `run_direct_rtk_lidar.ps1` | 从combined数据运行RTK直接标定和最终结果封装 |
+| `run_single_dataset.ps1` | 执行地面、两个GICP后端、精筛、共识和AX=XB求解 |
+| `view_result.ps1` | 打开3D运动对对比并打印数值增量 |
 
-最常用的 3D 入口：
-
-```powershell
-powershell.exe -NoProfile -ExecutionPolicy Bypass -File ".\run\view_result.ps1" `
-  -Frames "D:\你的数据目录\prepared\frames_all" `
-  -Pairs "D:\你的结果目录\B_consensus.npz" `
-  -Extrinsic "D:\你的结果目录\extrinsic.json" `
-  -PairIndex 0
-```
-
-`frames_all` 必须与生成 B 时的站点顺序一致。
+所有路径均为命令行参数；默认生成目录`work/`和`outputs/`不会提交Git。
diff --git a/run/export_legacy_stations.ps1 b/run/export_legacy_stations.ps1
deleted file mode 100644
index c577d7f..0000000
--- a/run/export_legacy_stations.ps1
+++ /dev/null
@@ -1,34 +0,0 @@
-param(
-    [Parameter(Mandatory = $true)][string]$DataRoot,
-    [Parameter(Mandatory = $true)][string]$OutputRoot,
-    [string]$LidarObject = "frontlidar",
-    [string]$Timezone = "+08:00",
-    [string[]]$StationNames = @(),
-    [int]$Stride = 1,
-    [double]$RtkMaxDtMs = 150.0
-)
-
-$ErrorActionPreference = "Stop"
-$Repo = Split-Path -Parent $PSScriptRoot
-$Exporter = Join-Path $Repo "tools\frontlidar_dlog_export.py"
-if (-not (Test-Path -LiteralPath $DataRoot)) { throw "DataRoot does not exist: $DataRoot" }
-if ($Stride -lt 1) { throw "Stride must be at least 1" }
-if ($StationNames.Count -gt 0) {
-    $Stations = @($StationNames | ForEach-Object { Get-Item -LiteralPath (Join-Path $DataRoot $_) })
-} else {
-    $Stations = @(Get-ChildItem -LiteralPath $DataRoot -Directory | Where-Object {
-        (Test-Path -LiteralPath (Join-Path $_.FullName "dobject")) -and
-        (Test-Path -LiteralPath (Join-Path $_.FullName "dobject_recording"))
-    } | Sort-Object Name)
-}
-if ($Stations.Count -eq 0) { throw "No station directory containing dobject and dobject_recording was found" }
-New-Item -ItemType Directory -Force -Path $OutputRoot | Out-Null
-foreach ($Station in $Stations) {
-    $Out = Join-Path $OutputRoot $Station.Name
-    Write-Host "[legacy station $($Station.Name)]"
-    & python $Exporter --dlog $Station.FullName --out $Out --object $LidarObject --format npz `
-        --timezone $Timezone --stride $Stride --compress --rtk-sidecars --write-reports --resume `
-        --rtk-max-dt-ms $RtkMaxDtMs
-    if ($LASTEXITCODE -ne 0) { throw "Export failed for station $($Station.Name)" }
-}
-Write-Host "Exported stations: $($Stations.Count)"
diff --git a/run/prepare_legacy_dataset.ps1 b/run/prepare_legacy_dataset.ps1
deleted file mode 100644
index 934f8f5..0000000
--- a/run/prepare_legacy_dataset.ps1
+++ /dev/null
@@ -1,21 +0,0 @@
-param(
-    [Parameter(Mandatory = $true)][string]$ExportRoot,
-    [Parameter(Mandatory = $true)][string]$Output,
-    [Parameter(Mandatory = $true)][double]$HeadingOffsetDeg,
-    [Parameter(Mandatory = $true)][double[]]$AntennaLever,
-    [int]$MinStations = 30,
-    [int]$ExpectedStations = 0,
-    [double]$HeadingStdLimitDeg = [double]::PositiveInfinity,
-    [switch]$Overwrite
-)
-
-$ErrorActionPreference = "Stop"
-if ($AntennaLever.Count -ne 3) { throw "AntennaLever must contain X,Y,Z in body coordinates" }
-$Repo = Split-Path -Parent $PSScriptRoot
-$Args = @((Join-Path $Repo "tools\prepare_station_dataset.py"), "--export-root", $ExportRoot,
-    "--output", $Output, "--heading-offset-deg", "$HeadingOffsetDeg", "--antenna-lever") +
-    @($AntennaLever | ForEach-Object { "$_" }) + @("--min-stations", "$MinStations",
-    "--expected-stations", "$ExpectedStations", "--heading-std-limit-deg", "$HeadingStdLimitDeg")
-if ($Overwrite) { $Args += "--overwrite" }
-& python @Args
-if ($LASTEXITCODE -ne 0) { throw "Legacy dataset preparation failed" }
diff --git a/run/prepare_multisensor_dataset.ps1 b/run/prepare_multisensor_dataset.ps1
index 28c57cf..a5b07a9 100644
--- a/run/prepare_multisensor_dataset.ps1
+++ b/run/prepare_multisensor_dataset.ps1
@@ -3,6 +3,7 @@ param(
     [Parameter(Mandatory = $true)][string]$Output,
     [Parameter(Mandatory = $true)][double]$HeadingOffsetDeg,
     [Parameter(Mandatory = $true)][double[]]$AntennaLever,
+    [string]$PoseName = "rtk_gga_raw_heading",
     [int]$MinStations = 30,
     [int]$ExpectedStations = 0,
     [double]$HeadingStdLimitDeg = 0.5,
@@ -13,7 +14,7 @@ $ErrorActionPreference = "Stop"
 if ($AntennaLever.Count -ne 3) { throw "AntennaLever must contain X,Y,Z in body coordinates" }
 $Repo = Split-Path -Parent $PSScriptRoot
 $Args = @((Join-Path $Repo "tools\prepare_multisensor_station_dataset.py"), "--combined-root", $CombinedRoot,
-    "--output", $Output, "--heading-offset-deg", "$HeadingOffsetDeg", "--antenna-lever") +
+    "--output", $Output, "--pose-name", $PoseName, "--heading-offset-deg", "$HeadingOffsetDeg", "--antenna-lever") +
     @($AntennaLever | ForEach-Object { "$_" }) + @("--min-stations", "$MinStations",
     "--expected-stations", "$ExpectedStations", "--heading-std-limit-deg", "$HeadingStdLimitDeg")
 if ($Overwrite) { $Args += "--overwrite" }
diff --git a/run/run_all.ps1 b/run/run_all.ps1
deleted file mode 100644
index 18d7ed7..0000000
--- a/run/run_all.ps1
+++ /dev/null
@@ -1,74 +0,0 @@
-param(
-    [Parameter(Mandatory = $true)][string]$Batch1Prepared,
-    [Parameter(Mandatory = $true)][string]$Batch2Prepared,
-    [string]$OutputRoot = ""
-)
-
-$ErrorActionPreference = "Stop"
-$Repo = Split-Path -Parent $PSScriptRoot
-if ([string]::IsNullOrWhiteSpace($OutputRoot)) {
-    $OutputRoot = Join-Path $Repo "results\01_previous_two_batches"
-}
-$Code = Join-Path $Repo "code\rigorous_calibration.py"
-$Refine = Join-Path $Repo "code\refine_pairs.py"
-$Summary = Join-Path $Repo "code\summarize_results.py"
-$B1Frames = Join-Path $Batch1Prepared "frames_all"
-$B2Frames = Join-Path $Batch2Prepared "frames_all"
-$B1Body = Join-Path $Batch1Prepared "body_poses_rear_gga_raw_rear_to_front.csv"
-$B2Body = Join-Path $Batch2Prepared "body_poses_rear_gga_raw_rear_to_front.csv"
-
-function Run-Python {
-    param([string]$Stage, [string[]]$Arguments)
-    Write-Host "[$Stage]"
-    & python @Arguments
-    if ($LASTEXITCODE -ne 0) { throw "$Stage failed with Python exit code $LASTEXITCODE" }
-}
-
-foreach ($Path in @($B1Frames, $B2Frames, $B1Body, $B2Body)) {
-    if (-not (Test-Path -LiteralPath $Path)) { throw "Input does not exist: $Path" }
-}
-$Common = Join-Path $OutputRoot "common"
-$Small = Join-Path $OutputRoot "small_gicp"
-$Open = Join-Path $OutputRoot "open3d_gicp"
-New-Item -ItemType Directory -Force -Path $Common,$Small,$Open | Out-Null
-
-Run-Python "batch2 ground planes" @($Code, "ground", "--frames", $B2Frames, "--output", (Join-Path $Common "ground_planes_batch2.csv"))
-
-foreach ($Backend in @("small_gicp", "open3d")) {
-    $Directory = if ($Backend -eq "small_gicp") { $Small } else { $Open }
-    $Extra = @()
-    if ($Backend -eq "open3d") { $Extra = @("--max-gap", "3", "--multistart", "1", "--iterations", "40") }
-    $B2Raw = Join-Path $Directory "B_batch2_estimation.npz"
-    $B2QualityJson = Join-Path $Directory "B_batch2_quality.json"
-    $B2QualityCsv = Join-Path $Directory "B_batch2_quality.csv"
-    Run-Python "$Backend batch2 pairs" (@($Code, "pairs", "--backend", $Backend, "--frames", $B2Frames, "--body", $B2Body,
-        "--output", $B2Raw, "--quality-json", $B2QualityJson, "--quality-csv", $B2QualityCsv) + $Extra)
-    $B2Refined = Join-Path $Directory "B_batch2_refined.npz"
-    Run-Python "$Backend batch2 refinement" @($Refine, "--pairs", $B2Raw, "--quality-json", $B2QualityJson, "--output", $B2Refined)
-    $Extrinsic = Join-Path $Directory "extrinsic_batch2_refined.json"
-    Run-Python "$Backend batch2 calibration" @($Code, "calibrate", "--pairs", $B2Refined,
-        "--ground-planes", (Join-Path $Common "ground_planes_batch2.csv"), "--output", $Extrinsic)
-
-    $B1Raw = Join-Path $Directory "B_batch1_auxiliary.npz"
-    $B1QualityJson = Join-Path $Directory "B_batch1_quality.json"
-    $B1QualityCsv = Join-Path $Directory "B_batch1_quality.csv"
-    Run-Python "$Backend batch1 auxiliary pairs" @($Code, "pairs", "--backend", $Backend, "--frames", $B1Frames, "--body", $B1Body,
-        "--output", $B1Raw, "--quality-json", $B1QualityJson, "--quality-csv", $B1QualityCsv,
-        "--max-gap", "3", "--multistart", "1", "--iterations", "40")
-    $B1Refined = Join-Path $Directory "B_batch1_auxiliary_refined.npz"
-    Run-Python "$Backend batch1 refinement" @($Refine, "--pairs", $B1Raw, "--quality-json", $B1QualityJson, "--output", $B1Refined)
-    Run-Python "$Backend batch1 auxiliary check" @($Code, "validate", "--pairs", $B1Refined,
-        "--extrinsic", $Extrinsic, "--output", (Join-Path $Directory "batch1_auxiliary_check.json"))
-}
-
-Run-Python "backend summary" @($Summary,
-    "--open3d", (Join-Path $Open "extrinsic_batch2_refined.json"),
-    "--small", (Join-Path $Small "extrinsic_batch2_refined.json"),
-    "--open3d-quality", (Join-Path $Open "B_batch2_quality.json"),
-    "--small-quality", (Join-Path $Small "B_batch2_quality.json"),
-    "--open3d-check", (Join-Path $Open "batch1_auxiliary_check.json"),
-    "--small-check", (Join-Path $Small "batch1_auxiliary_check.json"),
-    "--output", (Join-Path $OutputRoot "comparison_summary.json"),
-    "--recommended-output", (Join-Path $OutputRoot "final_extrinsic_recommended.json"))
-
-Write-Host "Two-batch results: $OutputRoot"
diff --git a/run/run_consensus_finish.ps1 b/run/run_consensus_finish.ps1
deleted file mode 100644
index f809b3d..0000000
--- a/run/run_consensus_finish.ps1
+++ /dev/null
@@ -1,34 +0,0 @@
-param([string]$ResultRoot = "")
-
-$ErrorActionPreference = "Stop"
-$Repo = Split-Path -Parent $PSScriptRoot
-if ([string]::IsNullOrWhiteSpace($ResultRoot)) { $ResultRoot = Join-Path $Repo "results\01_previous_two_batches" }
-$Code = Join-Path $Repo "code\rigorous_calibration.py"
-$Filter = Join-Path $Repo "code\cross_backend_filter.py"
-$Finalize = Join-Path $Repo "code\finalize_consensus.py"
-
-function Run-Python {
-    param([string[]]$Arguments)
-    & python @Arguments
-    if ($LASTEXITCODE -ne 0) { throw "Python failed with exit code $LASTEXITCODE" }
-}
-
-Run-Python @($Filter, "--open3d-pairs", (Join-Path $ResultRoot "open3d_gicp\B_batch2_refined.npz"),
-    "--small-pairs", (Join-Path $ResultRoot "small_gicp\B_batch2_refined.npz"),
-    "--output", (Join-Path $ResultRoot "consensus\B_batch2_consensus.npz"))
-Run-Python @($Filter, "--open3d-pairs", (Join-Path $ResultRoot "open3d_gicp\B_batch1_auxiliary_refined.npz"),
-    "--small-pairs", (Join-Path $ResultRoot "small_gicp\B_batch1_auxiliary_refined.npz"),
-    "--output", (Join-Path $ResultRoot "consensus\B_batch1_consensus.npz"), "--min-pairs", "15")
-Run-Python @($Code, "calibrate", "--pairs", (Join-Path $ResultRoot "consensus\B_batch2_consensus.npz"),
-    "--ground-planes", (Join-Path $ResultRoot "common\ground_planes_batch2.csv"),
-    "--output", (Join-Path $ResultRoot "consensus\extrinsic_batch2_consensus.json"))
-Run-Python @($Code, "validate", "--pairs", (Join-Path $ResultRoot "consensus\B_batch1_consensus.npz"),
-    "--extrinsic", (Join-Path $ResultRoot "consensus\extrinsic_batch2_consensus.json"),
-    "--output", (Join-Path $ResultRoot "consensus\batch1_auxiliary_check.json"))
-Run-Python @($Finalize,
-    "--consensus-extrinsic", (Join-Path $ResultRoot "consensus\extrinsic_batch2_consensus.json"),
-    "--consensus-check", (Join-Path $ResultRoot "consensus\batch1_auxiliary_check.json"),
-    "--open3d-extrinsic", (Join-Path $ResultRoot "open3d_gicp\extrinsic_batch2_refined.json"),
-    "--small-extrinsic", (Join-Path $ResultRoot "small_gicp\extrinsic_batch2_refined.json"),
-    "--output", (Join-Path $ResultRoot "final_extrinsic_recommended.json"),
-    "--summary", (Join-Path $ResultRoot "final_summary.json"))
diff --git a/LiDAR_RTK_Direct_Calibration/run/run_direct_rtk_lidar.ps1 b/run/run_direct_rtk_lidar.ps1
similarity index 100%
rename from LiDAR_RTK_Direct_Calibration/run/run_direct_rtk_lidar.ps1
rename to run/run_direct_rtk_lidar.ps1
diff --git a/LiDAR_RTK_Direct_Calibration/run/run_full_pipeline.ps1 b/run/run_full_pipeline.ps1
similarity index 100%
rename from LiDAR_RTK_Direct_Calibration/run/run_full_pipeline.ps1
rename to run/run_full_pipeline.ps1
diff --git a/run/run_sensitivity_scan.ps1 b/run/run_sensitivity_scan.ps1
deleted file mode 100644
index 8c66353..0000000
--- a/run/run_sensitivity_scan.ps1
+++ /dev/null
@@ -1,22 +0,0 @@
-param(
-    [int]$PairIndex = 0,
-    [string]$ResultRoot = ""
-)
-
-$ErrorActionPreference = "Stop"
-$Repo = Split-Path -Parent $PSScriptRoot
-if ([string]::IsNullOrWhiteSpace($ResultRoot)) { $ResultRoot = Join-Path $Repo "results\01_previous_two_batches" }
-$Code = Join-Path $Repo "code\scan_extrinsic_sensitivity.py"
-$X = Join-Path $ResultRoot "final_extrinsic_recommended.json"
-$Ground = Join-Path $ResultRoot "common\ground_planes_batch2.csv"
-$Out = Join-Path $ResultRoot "diagnostics"
-
-foreach ($Backend in @("open3d_gicp", "small_gicp")) {
-    $Label = if ($Backend -eq "open3d_gicp") { "open3d_refined" } else { "small_gicp_refined" }
-    & python $Code --pairs (Join-Path $ResultRoot "$Backend\B_batch2_refined.npz") --extrinsic $X `
-        --ground-planes $Ground --pair-index $PairIndex --output (Join-Path $Out "${Label}_pair${PairIndex}_left_rpy_scan.json")
-    if ($LASTEXITCODE -ne 0) { throw "$Backend sensitivity scan failed" }
-}
-& python $Code --pairs (Join-Path $ResultRoot "consensus\B_batch2_consensus.npz") --extrinsic $X `
-    --ground-planes $Ground --pair-index $PairIndex --output (Join-Path $Out "consensus_pair${PairIndex}_left_rpy_scan.json")
-if ($LASTEXITCODE -ne 0) { throw "Consensus sensitivity scan failed" }
diff --git a/run/run_single_dataset.ps1 b/run/run_single_dataset.ps1
index 13b8713..3bf3e53 100644
--- a/run/run_single_dataset.ps1
+++ b/run/run_single_dataset.ps1
@@ -1,8 +1,8 @@
 param(
     [Parameter(Mandatory = $true)][string]$Prepared,
     [Parameter(Mandatory = $true)][string]$OutputRoot,
-    [string]$PoseName = "rear_gga_raw_rear_to_front",
-    [double]$BodyHeight = 0.2335,
+    [string]$ReferencePoseFile = "reference_poses_rtk_gga_raw_heading.csv",
+    [double]$ReferenceHeight = 0.8535,
     [int]$MinPairs = 20,
     [int]$Bootstrap = 100
 )
@@ -13,7 +13,7 @@ $Code = Join-Path $Repo "code\rigorous_calibration.py"
 $Refine = Join-Path $Repo "code\refine_pairs.py"
 $Consensus = Join-Path $Repo "code\cross_backend_filter.py"
 $Frames = Join-Path $Prepared "frames_all"
-$Body = Join-Path $Prepared "body_poses_$PoseName.csv"
+$ReferencePoses = Join-Path $Prepared $ReferencePoseFile
 $Common = Join-Path $OutputRoot "common"
 $Open = Join-Path $OutputRoot "open3d_gicp"
 $Small = Join-Path $OutputRoot "small_gicp"
@@ -26,7 +26,7 @@ function Run-Python {
     if ($LASTEXITCODE -ne 0) { throw "$Stage failed with Python exit code $LASTEXITCODE" }
 }
 
-foreach ($Path in @($Frames, $Body)) {
+foreach ($Path in @($Frames, $ReferencePoses)) {
     if (-not (Test-Path -LiteralPath $Path)) { throw "Input does not exist: $Path" }
 }
 New-Item -ItemType Directory -Force -Path $Common,$Open,$Small,$ConsensusOut | Out-Null
@@ -39,7 +39,7 @@ foreach ($Backend in @("small_gicp", "open3d")) {
     $Raw = Join-Path $Directory "B_estimation.npz"
     $QualityJson = Join-Path $Directory "B_quality.json"
     $QualityCsv = Join-Path $Directory "B_quality.csv"
-    $PairArgs = @($Code, "pairs", "--backend", $Backend, "--frames", $Frames, "--body", $Body,
+    $PairArgs = @($Code, "pairs", "--backend", $Backend, "--frames", $Frames, "--reference-poses", $ReferencePoses,
                   "--output", $Raw, "--quality-json", $QualityJson, "--quality-csv", $QualityCsv,
                   "--min-pairs", "$MinPairs")
     if ($Backend -eq "open3d") { $PairArgs += @("--max-gap", "3", "--multistart", "1", "--iterations", "40") }
@@ -50,7 +50,7 @@ foreach ($Backend in @("small_gicp", "open3d")) {
     )
     Run-Python "$Backend calibration" @(
         $Code, "calibrate", "--pairs", (Join-Path $Directory "B_refined.npz"),
-        "--ground-planes", $Ground, "--body-height", "$BodyHeight",
+        "--ground-planes", $Ground, "--reference-height", "$ReferenceHeight",
         "--bootstrap", "$Bootstrap", "--output", (Join-Path $Directory "extrinsic.json")
     )
 }
@@ -63,7 +63,7 @@ Run-Python "cross-backend consensus" @(
 )
 Run-Python "consensus calibration" @(
     $Code, "calibrate", "--pairs", $ConsensusPairs, "--ground-planes", $Ground,
-    "--body-height", "$BodyHeight", "--bootstrap", "$Bootstrap",
+    "--reference-height", "$ReferenceHeight", "--bootstrap", "$Bootstrap",
     "--output", (Join-Path $ConsensusOut "extrinsic.json")
 )
 
diff --git a/tools/README.md b/tools/README.md
index 0c56399..c670433 100644
--- a/tools/README.md
+++ b/tools/README.md
@@ -1,26 +1,11 @@
-# tools
+# tools目录
 
-本目录负责从原始 dlog/rscap 导出 NPZ、关联 RTK/IMU 并生成 prepared；完整流程和参数统一见仓库根目录 `README.md`。
-
-| 文件 | 作用 |
+| 文件 | 输入→输出 |
 |---|---|
-| `frontlidar_dlog_export.py` | 从单个 Medulla dlog 导出原始 LiDAR NPZ，可匹配站内 RTK。 |
-| `prepare_station_dataset.py` | 旧式逐站导出生成 prepared。 |
-| `build_multisensor_npz.py` | 以 LiDAR 帧为索引关联独立 RTK/IMU。 |
-| `prepare_multisensor_station_dataset.py` | combined NPZ 生成 prepared。 |
-| `rscap_v2/capture_format_v2.py` | 读取 rscap v2。 |
-| `rscap_v2/audit_capture_v2.py` | 审计 capture 完整性。 |
-| `rscap_v2/parse_rtk_imu_v2.py` | 解析 RTK/IMU 为 JSONL。 |
-| `rscap_v2/pipeline_common*.py` | 时间和协议解析共用逻辑。 |
+| `frontlidar_dlog_export.py` | LiDAR dlog → 逐帧原始点云NPZ；时间来自DObject post tick |
+| `rscap_v2/parse_rtk_imu_v2.py` | RTK/IMU rscap → JSONL，保存校验状态、主机时间、GNSS/IMU设备字段和原始报文 |
+| `rscap_v2/audit_capture_v2.py` | 检查rscap结构、时间范围和记录统计 |
+| `build_multisensor_npz.py` | 按LiDAR帧最近邻关联GGA/heading，并附加IMU时间窗 → combined NPZ |
+| `prepare_multisensor_station_dataset.py` | combined NPZ → 每站一帧`frames_all`和`reference_poses_*.csv` |
 
-统一输出接口：
-
-```text
-prepared/
-  frames_all/station_*.npz
-  body_poses_rear_gga_raw_rear_to_front.csv
-  station_summary.csv
-  manifest.json
-```
-
-后续配准必须使用 `points_raw`，不能使用已经由某套外参变换后的点云。
+当前标定只使用LiDAR和RTK；IMU保持原始传感器坐标，不参与点云去畸变或外参求解。prepared阶段对站内有效RTK取平均、对heading取圆均值，并选择有效帧序列的中间LiDAR帧。
diff --git a/tools/prepare_multisensor_station_dataset.py b/tools/prepare_multisensor_station_dataset.py
index 0cc3ce1..c47fdc5 100644
--- a/tools/prepare_multisensor_station_dataset.py
+++ b/tools/prepare_multisensor_station_dataset.py
@@ -1,5 +1,5 @@
 #!/usr/bin/env python3
-"""Prepare one static LiDAR frame and one yaw-only RTK body pose per NPZ segment."""
+"""Prepare one static LiDAR frame and one yaw-only RTK reference pose per NPZ segment."""
 
 from __future__ import annotations
 
@@ -66,7 +66,7 @@ def parse_args() -> argparse.Namespace:
     parser = argparse.ArgumentParser(description=__doc__)
     parser.add_argument("--combined-root", type=Path, required=True)
     parser.add_argument("--output", type=Path, required=True)
-    parser.add_argument("--pose-name", default="rear_gga_raw_rear_to_front")
+    parser.add_argument("--pose-name", default="rtk_gga_raw_heading")
     parser.add_argument("--heading-offset-deg", type=float, required=True)
     parser.add_argument("--antenna-lever", type=float, nargs=3, required=True, metavar=("X", "Y", "Z"))
     parser.add_argument("--accepted-fixes", type=int, nargs="+", default=[4, 5])
@@ -140,12 +140,12 @@ def main() -> int:
                               origin["lat"], origin["lon"])
         corrected_heading = (item["heading"] + args.heading_offset_deg) % 360.0
         yaw = math.radians(90.0 - corrected_heading)
-        body = antenna - yaw_rotation(yaw) @ lever
-        pose_rows.append(dict(zip(POSE_FIELDS, [item["time"], *body, 0.0, 0.0,
+        reference_position = antenna - yaw_rotation(yaw) @ lever
+        pose_rows.append(dict(zip(POSE_FIELDS, [item["time"], *reference_position, 0.0, 0.0,
                                                 math.sin(yaw / 2.0), math.cos(yaw / 2.0)])))
         summaries[index - 1].update({"sequence": index, "prepared_frame": destination.name,
                                      "corrected_heading_deg": corrected_heading})
-    pose_path = args.output / f"body_poses_{args.pose_name}.csv"
+    pose_path = args.output / f"reference_poses_{args.pose_name}.csv"
     with pose_path.open("w", encoding="utf-8", newline="") as stream:
         writer = csv.DictWriter(stream, fieldnames=POSE_FIELDS); writer.writeheader(); writer.writerows(pose_rows)
     with (args.output / "station_summary.csv").open("w", encoding="utf-8", newline="") as stream:
@@ -154,7 +154,7 @@ def main() -> int:
     document = {"source_combined_root": str(args.combined_root.resolve()), "station_count": len(selected),
                 "rejected": rejected, "pose_csv": pose_path.name,
                 "selection_policy": "middle LiDAR frame among fixed-position and valid-heading associations",
-                "body_pose_configuration": {"raw_heading_offset_deg": args.heading_offset_deg,
+                "reference_pose_configuration": {"raw_heading_offset_deg": args.heading_offset_deg,
                     "antenna_lever_body_m": args.antenna_lever,
                     "orientation_model": "yaw-only, identical to the previous calibration workflow"},
                 "stations": [{"sequence": i + 1, "source_station": item["station"],
diff --git a/tools/prepare_station_dataset.py b/tools/prepare_station_dataset.py
deleted file mode 100644
index 3cdf419..0000000
--- a/tools/prepare_station_dataset.py
+++ /dev/null
@@ -1,194 +0,0 @@
-#!/usr/bin/env python3
-"""Prepare one static LiDAR frame and one yaw-only RTK body pose per station."""
-
-from __future__ import annotations
-
-import argparse
-import csv
-import json
-import math
-import re
-import shutil
-import sys
-from pathlib import Path
-from typing import Any
-
-import numpy as np
-
-POSE_FIELDS = ["time", "x", "y", "z", "qx", "qy", "qz", "qw"]
-
-
-def parse_args() -> argparse.Namespace:
-    parser = argparse.ArgumentParser(
-        description="Select one static LiDAR frame per exported station and rebuild yaw-only RTK body poses."
-    )
-    parser.add_argument("--export-root", type=Path, required=True, help="Directory containing exported station directories.")
-    parser.add_argument("--output", type=Path, required=True, help="Output prepared directory.")
-    parser.add_argument("--pose-name", default="rear_gga_raw_rear_to_front", help="Suffix of body_poses_<name>.csv.")
-    parser.add_argument("--heading-offset-deg", type=float, required=True, help="Added to raw_heading_deg before ENU yaw conversion.")
-    parser.add_argument("--antenna-lever", type=float, nargs=3, metavar=("X", "Y", "Z"), required=True, help="Antenna position in body coordinates [m].")
-    parser.add_argument("--expected-stations", type=int, default=0, help="Require exactly this many usable stations; 0 disables.")
-    parser.add_argument("--min-stations", type=int, default=30, help="Fail below this many usable stations.")
-    parser.add_argument("--groups", nargs="*", default=None, help="Optional explicit station directory names.")
-    parser.add_argument("--accepted-fixes", type=int, nargs="+", default=[4, 5], help="Accepted GGA fix values.")
-    parser.add_argument("--heading-std-limit-deg", type=float, default=float("inf"), help="Reject a station above this heading circular stddev.")
-    parser.add_argument("--overwrite", action="store_true", help="Allow replacing generated files in a non-empty output directory.")
-    return parser.parse_args()
-
-
-def truth(value: Any) -> bool:
-    return str(value).strip().lower() in {"1", "true", "yes", "y"}
-
-
-def natural_key(value: str) -> list[Any]:
-    return [int(part) if part.isdigit() else part.lower() for part in re.split(r"(\d+)", value)]
-
-def read_csv(path: Path) -> list[dict[str, str]]:
-    with path.open("r", encoding="utf-8-sig", newline="") as stream:
-        return list(csv.DictReader(stream))
-
-
-def require_columns(rows: list[dict[str, str]], path: Path, columns: list[str]) -> None:
-    if not rows:
-        raise ValueError(f"{path}: no rows")
-    missing = [column for column in columns if column not in rows[0]]
-    if missing:
-        raise ValueError(f"{path}: missing required columns: {', '.join(missing)}")
-
-
-def circular_mean_deg(values: np.ndarray) -> float:
-    radians = np.deg2rad(values)
-    return float(np.rad2deg(math.atan2(float(np.mean(np.sin(radians))), float(np.mean(np.cos(radians))))) % 360.0)
-
-
-def circular_std_deg(values: np.ndarray) -> float:
-    radians = np.deg2rad(values)
-    resultant = max(math.hypot(float(np.mean(np.cos(radians))), float(np.mean(np.sin(radians)))), 1e-12)
-    return float(np.rad2deg(math.sqrt(-2.0 * math.log(resultant))))
-
-
-def geodetic_to_ecef(lat_deg: float, lon_deg: float, height_m: float) -> np.ndarray:
-    a, e2 = 6378137.0, 6.69437999014e-3
-    lat, lon = math.radians(lat_deg), math.radians(lon_deg)
-    sin_lat, cos_lat, sin_lon, cos_lon = math.sin(lat), math.cos(lat), math.sin(lon), math.cos(lon)
-    n = a / math.sqrt(1.0 - e2 * sin_lat * sin_lat)
-    return np.array([(n + height_m) * cos_lat * cos_lon, (n + height_m) * cos_lat * sin_lon, (n * (1.0 - e2) + height_m) * sin_lat], dtype=float)
-
-
-def ecef_to_enu(ecef: np.ndarray, origin_ecef: np.ndarray, origin_lat_deg: float, origin_lon_deg: float) -> np.ndarray:
-    lat, lon = math.radians(origin_lat_deg), math.radians(origin_lon_deg)
-    sin_lat, cos_lat, sin_lon, cos_lon = math.sin(lat), math.cos(lat), math.sin(lon), math.cos(lon)
-    rotation = np.array([[-sin_lon, cos_lon, 0.0], [-sin_lat * cos_lon, -sin_lat * sin_lon, cos_lat], [cos_lat * cos_lon, cos_lat * sin_lon, sin_lat]], dtype=float)
-    return rotation @ (ecef - origin_ecef)
-
-
-def yaw_rotation(yaw: float) -> np.ndarray:
-    c, s = math.cos(yaw), math.sin(yaw)
-    return np.array([[c, -s, 0.0], [s, c, 0.0], [0.0, 0.0, 1.0]], dtype=float)
-
-
-def select_frame(station: Path) -> tuple[dict[str, str], int, int]:
-    path = station / "reports" / "manifest.csv"
-    rows = read_csv(path)
-    require_columns(rows, path, ["status", "unix_time_ns", "output_file"])
-    exported = [row for row in rows if row["status"] in {"exported", "resumed"}]
-    if not exported:
-        raise ValueError(f"{station.name}: no exported/resumed LiDAR frames")
-    valid = [row for row in exported if truth(row.get("rtk_position_valid")) and truth(row.get("rtk_heading_valid"))]
-    candidates = valid or exported
-    candidates.sort(key=lambda row: int(row["unix_time_ns"]))
-    return candidates[len(candidates) // 2], len(exported), len(valid)
-
-
-def validation_checks(station: Path) -> dict[str, bool]:
-    path = station / "reports" / "validation_report.json"
-    if not path.exists():
-        return {}
-    document = json.loads(path.read_text(encoding="utf-8"))
-    return {str(item.get("name")): bool(item.get("ok")) for item in document.get("checks", [])}
-
-
-def process_station(station: Path, args: argparse.Namespace) -> tuple[dict[str, Any], dict[str, Any]]:
-    rtk_path = station / "rtk" / "gps_post_z.csv"
-    rows = read_csv(rtk_path)
-    columns = ["lat", "lon", "alt_m", "raw_heading_deg", "fix", "position_valid", "heading_valid", "unix_time_ns"]
-    require_columns(rows, rtk_path, columns)
-    fixes = set(args.accepted_fixes)
-    good = [row for row in rows if truth(row["position_valid"]) and truth(row["heading_valid"]) and int(row["fix"]) in fixes]
-    if not good:
-        raise ValueError(f"{station.name}: no RTK samples pass position/heading/fix filters")
-    lat = np.asarray([float(row["lat"]) for row in good])
-    lon = np.asarray([float(row["lon"]) for row in good])
-    alt = np.asarray([float(row["alt_m"]) for row in good])
-    heading = np.asarray([float(row["raw_heading_deg"]) for row in good])
-    times = np.asarray([int(row["unix_time_ns"]) for row in good], dtype=np.int64)
-    heading_std = circular_std_deg(heading)
-    if heading_std > args.heading_std_limit_deg:
-        raise ValueError(f"{station.name}: heading circular stddev {heading_std:.3f} deg exceeds {args.heading_std_limit_deg:.3f} deg")
-    frame, frame_count, valid_frame_count = select_frame(station)
-    source = station / frame["output_file"]
-    if not source.is_file():
-        raise FileNotFoundError(f"{station.name}: selected frame is absent: {source}")
-    checks = validation_checks(station)
-    selected = {"station": station.name, "source_frame": source, "frame_time": int(frame["unix_time_ns"]) / 1e9, "lat_deg": float(np.mean(lat)), "lon_deg": float(np.mean(lon)), "alt_m": float(np.mean(alt)), "raw_heading_deg": circular_mean_deg(heading), "raw_heading_std_deg": heading_std}
-    summary = {"station": station.name, "selected_frame": frame["output_file"], "exported_frames": frame_count, "frames_with_valid_rtk": valid_frame_count, "valid_rtk_samples": len(good), "raw_heading_mean_deg": selected["raw_heading_deg"], "raw_heading_std_deg": heading_std, "alt_std_m": float(np.std(alt)), "rtk_span_sec": float((times.max() - times.min()) / 1e9) if len(times) > 1 else 0.0, "payload_ok": checks.get("lidar_payload_length", ""), "rtk_parse_ok": checks.get("gps_post_z_parse", ""), "time_check_3s_ok": checks.get("rtk_time_alignment", "")}
-    return selected, summary
-
-
-def main() -> int:
-    args = parse_args()
-    if args.min_stations < 2 or args.expected_stations < 0:
-        raise ValueError("--min-stations must be >=2 and --expected-stations must be >=0")
-    if not args.export_root.is_dir():
-        raise NotADirectoryError(args.export_root)
-    names = args.groups or [path.name for path in args.export_root.iterdir() if path.is_dir()]
-    stations = [args.export_root / name for name in sorted(names, key=natural_key)]
-    missing = [str(path) for path in stations if not path.is_dir()]
-    if missing:
-        raise FileNotFoundError("station directories do not exist: " + ", ".join(missing))
-    selected, summaries, rejected = [], [], []
-    for station in stations:
-        try:
-            item, summary = process_station(station, args)
-            selected.append(item); summaries.append(summary)
-        except (ValueError, FileNotFoundError) as error:
-            rejected.append({"station": station.name, "reason": str(error)})
-    if args.expected_stations and len(selected) != args.expected_stations:
-        raise RuntimeError(f"expected {args.expected_stations} usable stations, got {len(selected)}; rejected={rejected}")
-    if len(selected) < args.min_stations:
-        raise RuntimeError(f"need at least {args.min_stations} usable stations, got {len(selected)}; rejected={rejected}")
-    output, frames_dir = args.output, args.output / "frames_all"
-    if output.exists() and any(output.iterdir()) and not args.overwrite:
-        raise FileExistsError(f"{output} is non-empty; pass --overwrite to replace generated files")
-    frames_dir.mkdir(parents=True, exist_ok=True)
-    origin = selected[0]
-    origin_ecef = geodetic_to_ecef(origin["lat_deg"], origin["lon_deg"], origin["alt_m"])
-    lever = np.asarray(args.antenna_lever, dtype=float)
-    pose_rows = []
-    for index, item in enumerate(selected, 1):
-        destination = frames_dir / f"station_{index:02d}.npz"
-        shutil.copy2(item["source_frame"], destination)
-        antenna_enu = ecef_to_enu(geodetic_to_ecef(item["lat_deg"], item["lon_deg"], item["alt_m"]), origin_ecef, origin["lat_deg"], origin["lon_deg"])
-        corrected_heading = (item["raw_heading_deg"] + args.heading_offset_deg) % 360.0
-        yaw = math.radians(90.0 - corrected_heading)
-        body_position = antenna_enu - yaw_rotation(yaw) @ lever
-        pose_rows.append(dict(zip(POSE_FIELDS, [item["frame_time"], *body_position, 0.0, 0.0, math.sin(yaw / 2.0), math.cos(yaw / 2.0)])))
-        summaries[index - 1].update({"sequence": index, "prepared_frame": destination.name, "corrected_heading_deg": corrected_heading})
-    pose_path = output / f"body_poses_{args.pose_name}.csv"
-    with pose_path.open("w", encoding="utf-8", newline="") as stream:
-        writer = csv.DictWriter(stream, fieldnames=POSE_FIELDS); writer.writeheader(); writer.writerows(pose_rows)
-    fields = sorted({key for row in summaries for key in row})
-    with (output / "station_summary.csv").open("w", encoding="utf-8", newline="") as stream:
-        writer = csv.DictWriter(stream, fieldnames=fields); writer.writeheader(); writer.writerows(summaries)
-    manifest = {"source_export_root": str(args.export_root.resolve()), "station_count": len(selected), "pose_csv": pose_path.name, "frame_directory": "frames_all", "selection_policy": "middle frame among exported frames with valid RTK; falls back to middle exported frame", "rtk_filter": {"position_valid": True, "heading_valid": True, "accepted_fixes": args.accepted_fixes, "heading_std_limit_deg": args.heading_std_limit_deg}, "body_pose_configuration": {"raw_heading_offset_deg": args.heading_offset_deg, "antenna_lever_body_m": args.antenna_lever, "body_axes": "x forward, y left, z up; origin must match the supplied lever", "orientation_model": "yaw-only from raw_heading_deg; this tool does not reconstruct RTK pitch or roll"}, "enu_origin": {"lat_deg": origin["lat_deg"], "lon_deg": origin["lon_deg"], "alt_m": origin["alt_m"]}, "stations": [{"sequence": index + 1, "source_station": item["station"], "source_frame": str(item["source_frame"]), "prepared_frame": f"station_{index + 1:02d}.npz"} for index, item in enumerate(selected)]}
-    (output / "manifest.json").write_text(json.dumps(manifest, ensure_ascii=False, indent=2), encoding="utf-8")
-    print(json.dumps({"prepared": str(output.resolve()), "stations": len(selected), "rejected": rejected, "pose_csv": pose_path.name}, ensure_ascii=False, indent=2))
-    return 0
-
-
-if __name__ == "__main__":
-    try:
-        raise SystemExit(main())
-    except Exception as error:
-        print(f"ERROR: {error}", file=sys.stderr)
-        raise