顾及随机误差的地面三维激光扫描仪自检校模型及其抗差解法  

Self-Calibration Model of Terrestrial Three-Dimensional Laser Scanners Considering Random Errors and Robust Estimation Solution

作　　者：周腾飞 程效军 黄凯 陶远[3] Zhou Tengfei;Cheng Xiaojun;Huang Kai;Tao Yuan(College of Surveying and Geo-Informatics,Tongji University,Shanghai 200092,China;Key Laboratory of Advanced Engineering Surveying Ministry of Natural Resources,Shanghai 200092,China;School of Spatial Information and Geomatics Engineering,Anhui University of Science and Technology,Huainan,Anhui 232001,China)

机构地区：[1]同济大学测绘与地理信息学院,上海200092 [2]自然资源部现代工程测量重点实验室,上海200092 [3]安徽理工大学空间信息与测绘工程学院,安徽淮南232001

出　　处：《中国激光》2021年第13期89-101,共13页Chinese Journal of Lasers

基　　金：国家自然科学基金(41974213,41671449)。

摘　　要：针对地面三维激光扫描仪自检校模型易受到随机误差与粗差的影响,基于Gauss-Helmert坐标转换模型与扫描仪观测原理提出了一种三维激光扫描仪的自检校方法。该方法共包含6个外部转换参数与5个系统误差参数(附加参数),首先利用泰勒级数对函数模型进行线性化,并构造拉格朗日目标函数,基于Newton-Gauss法迭代求解所有未知参数的初值;之后利用标准化残差构造权因子函数,以对观测值进行重新定权,并通过迭代计算出参数的最终解。通过仿真和实验进行验证,结果表明所提方法较现有的算法能有效去除观测值中的随机误差与粗差,且具有良好的鲁棒性。Objective As an emerging technology, terrestrial laser scanners(TLSs) are used in various applications in forest resource surveys, reverse engineering, and measurement modeling. The original observations, distances, and angles of a TLS are easily affected by the external environment and instrument itself during acquisition, so the geometric information of a TLS often contains certain systematic errors in addition to random and gross errors. Thus, a TLS cannot completely reflect the real characteristics of the target objects directly related to the subsequent processing and applications. Therefore, it is necessary to effectively remove or correct the errors contained in the original observations of the point cloud data, which is also known as the calibration methodology. The traditional method usually separates the distance and angle, i.e., using a TLS to measure multiple fixed-length baselines or angles, solving the systematic error based on the theory of least squares. However, the above methods cannot completely remove the random and gross errors located in datasets. In this study, a new TLS self-calibration method was proposed by incorporating random and systematic errors into the function model as unknown parameters via the scanner observation principle and Gauss-Helmert model. The method can effectively consider all kinds of errors in the geometric information, and the results show that this method can efficiently remove random and gross errors with good robustness via simulation experiments and verification analysis of the measured data.Methods In this study,a self-calibration function model was proposed based on the scanner observation principle and Gauss-Helmert model;the corresponding additional parameters(APs),random errors of the original observations,and exterior orientation parameters(EOPs)were rationally appended to this model.In addition,a stochastic model conforming to the normal distribution was implemented according to the nominal accuracy of the original observations.The functional model was no

关 键 词：探测器 自检校 Gauss-Helmert模型 Newton-Gauss法 随机模型 抗差估计 

分 类 号：TN958.98[电子电信—信号与信息处理]