基于蒙特卡洛仿真的无人机机载LiDAR点云精度预估  

Accuracy Estimation of UAV-borne LiDAR Point Cloud Based on the Monte Carlo

作　　者：刘亚萍 明洋[1] 王刊生[1] 张霄[1] LIU Yaping;MING Yang;WANG Kansheng;ZHANG Xiao(CCCC Second Highway Consultants Co.,Ltd.,Wuhan 430056,China)

机构地区：[1]中交第二公路勘察设计研究院有限公司,湖北武汉430056

出　　处：《地理空间信息》2023年第1期74-78,共5页Geospatial Information

基　　金：中交第二公路勘察设计研究院有限公司科技研发资助项目(KJFZ-2016-065,KJFZ-2017-046,KJFZ-2018-043)。

摘　　要：受多种因素的综合影响,传统基于定位误差传播方程的方法难以对无人机机载LiDAR点云精度进行准确预估。鉴于此,提出了一种基于蒙特卡洛仿真的无人机机载LiDAR点云精度预估方法,通过蒙特卡洛仿真,直接分析误差源对点云坐标精度的影响。该方法不仅可以预估误差源对激光点云的整体精度影响,而且可对点云精度影响的空间分布规律进行直观分析。实际工程项目应用结果表明,预估精度与工程实际精度吻合较好,验证了方法的有效性。该方法可为激光测量项目的精度预估、设备选型提供有效依据,具有显著的社会和经济效益。It’s really hard to estimate the accuracy of UAV-borne LiDAR point cloud precisely based on the traditional positioning error equation method due to many complex systemic errors.In this paper,we proposed an accuracy estimation method of UAV-borne LiDAR point cloud based on the Monte Carlo.We calculated the relationship between error source and the 3D coordinates of point cloud directly by Monte Carlo.The method can not only estimate the accuracy of point cloud precisely,but also analyze the spatial distribution of accuracy intuitively.The experimental result indicates that the estimated accuracy is in good agreement with the actual accuracy,which verifies the feasibility of this method.It can provide effective evidence of accuracy estimation as well as equipment selection,which has notable social and economic benefits.

关 键 词：无人机机载LiDAR 蒙特卡洛仿真 精度预估 角元素误差 

分 类 号：P231[天文地球—摄影测量与遥感]