高精度激光点云配准驱动的毫米级地表形变检测方法

doi:10.11947/j.AGCS.2026.20250549

测绘学报 ›› 2026, Vol. 55 ›› Issue (5): 866-880.doi: 10.11947/j.AGCS.2026.20250549

高精度激光点云配准驱动的毫米级地表形变检测方法

韦朋成¹^,²(), 蒋贵宇¹^,², 沈航毅¹^,², 黄海峰¹^,², 张溶玲³()

^1.防灾减灾湖北省重点实验室（三峡大学），湖北　宜昌　443002
^2.三峡大学土木与建筑学院，湖北　宜昌　443002
^3.香港理工大学土地测量及地理资讯学系，香港　999077

收稿日期:2025-12-29 修回日期:2026-05-10 出版日期:2026-06-23 发布日期:2026-06-23
通讯作者: 张溶玲 E-mail:weipengcheng@ctgu.edu.cn;rongling.zhang@connect.polyu.hk
作者简介:韦朋成（1993—），男，博士，讲师，研究方向为时空数据处理与三维重建。　E-mail：weipengcheng@ctgu.edu.cn
基金资助:
湖北省自然科学基金(2025ABF104);防灾减灾湖北省重点实验室（三峡大学）开放基金(2025KJZ06)

Millimeter-level surface deformation detection method based on high-precision laser point cloud registration

Pengcheng WEI¹^,²(), Guiyu JIANG¹^,², Hangyi SHEN¹^,², Haifeng HUANG¹^,², Rongling ZHANG³()

^1.Hubei Key Laboratory of Disaster Prevention and Mitigation (China Three Gorges University), Yichang 443002, China
^2.College of Civil Engineering and Architecture, China Three Gorges University, Yichang 443002, China
^3.Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University, Hong Kong 999077, China

Received:2025-12-29 Revised:2026-05-10 Online:2026-06-23 Published:2026-06-23
Contact: Rongling ZHANG E-mail:weipengcheng@ctgu.edu.cn;rongling.zhang@connect.polyu.hk
About author:WEI Pengcheng (1993—), male, PhD, lecturer, majors in spatio-temporal data processing and 3D reconstruction.　E-mail: weipengcheng@ctgu.edu.cn
Supported by:
Hubei Provincial Natural Science Foundation of China(2025ABF104);Hubei Key Laboratory of Disaster Prevention and Mitigation (China Three Gorges University) Open Fund Project(2025KJZ06)

摘要/Abstract

摘要：

针对地质灾害监测中激光点云配准特征误匹配率高、稳健性差，以及海量离散点云中微小形变难以与植被干扰、环境噪声有效区分的难题，本文提出一种由粗到精的高精度激光点云配准驱动的毫米级地表形变检测方法。首先，利用图论构建可靠性度量剔除特征匹配粗差，并设计增强的GNC-Welsch稳健估计器，解决高粗差率下稳健估计目标函数的非凸优化难题；进而基于微观结构混合特征因子驱动实现高精度配准。在此基础上，提出精确提取与多维验证的形变检测策略：利用特征分析滤除植被干扰并提取形变候选区域，构建融合几何形态、统计分布及物理机理特征的多维验证框架，以剔除虚假形变。模拟试验表明，本文方法在不同形变量级下的均方根误差（RMSE）稳定在0.52~0.61 mm，在5 mm微小形变量下F₁值达86.11%，8 mm形变量下F₁值达95.39%，验证了该方法在毫米级形变检测中的有效性；真实边坡场景试验证实，本文方法能有效拒绝伪形变聚类，精准识别出15 mm的地表沉降与22.6 mm的地表隆起，验证了其在复杂野外环境下的稳健性与实用性。

关键词: 点云配准, 稳健估计, 地表形变检测

Abstract:

Addressing the challenges of high feature mismatch rates and poor robustness in laser point cloud registration for geological hazard monitoring, as well as difficulty in distinguishing subtle deformations from vegetation interference and environmental noise, this paper proposes a millimeter-level surface deformation detection method driven by coarse-to-fine high-precision laser point cloud registration. First, graph theory is used to eliminate gross errors in feature matching, and an enhanced GNC-Welsch robust estimator is designed to prevent coarse registration from falling into local minima. High-precision registration is then achieved using microstructure-based hybrid feature factors. A “precise extraction-multi-dimensional verification” strategy is proposed: feature analysis filters vegetation interference and extracts candidate deformation regions, while a multi-dimensional verification framework integrating geometric, statistical, and physical features eliminates false deformations. Simulation experiments show the method maintains RMSE of 0.52~0.61 mm across different deformation magnitudes, achieving F₁ scores of 86.11% and 95.39% at deformation magnitudes of 5 mm and 8 mm respectively, validating its effectiveness for millimeter-level deformation detection. Real slope experiments confirm the algorithm effectively rejects false deformation clusters and accurately identifies 15 mm ground subsidence and 22.6 mm ground uplift, validating its robustness and practicability in complex field environments.

Key words: point cloud registration, robust estimation, surface deformation detection

中图分类号:

P237

韦朋成, 蒋贵宇, 沈航毅, 黄海峰, 张溶玲. 高精度激光点云配准驱动的毫米级地表形变检测方法[J]. 测绘学报, 2026, 55(5): 866-880.

Pengcheng WEI, Guiyu JIANG, Hangyi SHEN, Haifeng HUANG, Rongling ZHANG. Millimeter-level surface deformation detection method based on high-precision laser point cloud registration[J]. Acta Geodaetica et Cartographica Sinica, 2026, 55(5): 866-880.

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链接本文: http://xb.chinasmp.com/CN/10.11947/j.AGCS.2026.20250549

http://xb.chinasmp.com/CN/Y2026/V55/I5/866

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d_max/m	分类性能			形变检测精度
d_max/m	精确度/（%）	召回率/（%）	F₁值/（%）	IoU/（%）	MAE/mm	RMSE/mm
0.005	100	75.60	86.11	75.60	0.33	0.52
0.006	100	83.68	91.11	83.68	0.33	0.52
0.007	100	88.77	94.05	88.77	0.34	0.52
0.008	100	91.19	95.39	91.19	0.34	0.52
0.01	100	91.49	95.56	91.49	0.33	0.52
0.02	100	96.45	98.19	96.45	0.35	0.54
0.05	100	98.49	99.24	98.49	0.33	0.53
0.1	100	98.39	99.19	98.39	0.35	0.61

聚类ID	点数	平均位移/mm	面积/m²	紧致度	位移标准差比例	梯度最大值	空间连续性	综合置信度/（%）	验证结果
S-0	895	－15.0	0.112	18.3	0.182	3.6	0.101	63.6	通过
S-1	707	－15.1	0.089	19.7	0.143	3.9	0.124	63.2	通过
S-2	646	－168.0	0.026	－	－	－	－	0	拒绝
U-0	810	17.3	0.095	21.5	0.217	6.8	0.068	54.3	拒绝
U-1	566	22.6	0.073	17.6	0.220	4.2	0.150	66.4	通过

统计指标	耗时/s	占比/（%）
预处理	14.52	45.8
粗配准	0.19	0.6
精配准	0.05	0.2
形变计算	16.77	52.9
多维验证	0.14	0.4
全流程总计	31.68	100

方法	配准重叠率/（%）	重叠区均值P2Pl/mm	初始形变点数	有效聚类数	有效形变点数
M1	47.21	5.06	3 115 409	－	－
M2	47.21	5.06	3 076 770	－	－
M3	47.21	5.06	3 076 770	35	40 218
M4	81.87	1.73	383 734	－	－
M5	81.87	1.73	129 011	3	2168

高精度激光点云配准驱动的毫米级地表形变检测方法

Millimeter-level surface deformation detection method based on high-precision laser point cloud registration

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