测绘通报 ›› 2020, Vol. 0 ›› Issue (12): 37-41.doi: 10.13474/j.cnki.11-2246.2020.0386

• 学术研究 • 上一篇    下一篇

基于IGS站组网的移动激光雷达测量系统整体检校

郭明1,2, 周腾飞1, 王国利1,2, 闫冰男1, 黄明1,2   

  1. 1. 北京建筑大学测绘与城市空间信息学院, 北京 100044;
    2. 代表性建筑与古建筑数据教育部工程研究中心, 北京 102616
  • 收稿日期:2020-02-20 修回日期:2020-04-23 出版日期:2020-12-25 发布日期:2021-01-06
  • 通讯作者: 黄明。E-mail:hmbak@126.com E-mail:hmbak@126.com
  • 作者简介:郭明(1981-),男,博士生,副教授,主要研究方向为移动测量技术、三维地理信息管理与可视化、建筑健康监测、低空无人机测绘应用技术。E-mail:guoming@bucea.edu.cn
  • 基金资助:
    国家自然科学基金(41971350);北京市教委科研项目-科技计划一般项目(面上项目KM201810016013);北京市未来城市设计高精尖创新中心项目(UDC2019031724);北京市属高校基本科研业务费(X18050;X18001);北京建筑大学校设科研基金自然科学项目特设基金(KYJJ2017024)

Overall calibration of mobile lidar measurement system based on IGS station networking

GUO Ming1,2, ZHOU Tengfei1, WANG Guoli1,2, YAN Bingnan1, HUANG Ming1,2   

  1. 1. School of Geomatics and Urban Information, Beijing University of Civil Engineering and Architecture, Beijing 100044, China;
    2. Engineering Research Center of Representative Building and Architectural Heritage Database Ministry of Education, Beijing 102616, China
  • Received:2020-02-20 Revised:2020-04-23 Online:2020-12-25 Published:2021-01-06

摘要: 针对车载移动测量系统中激光扫描仪和载体坐标系之间存在的位置和姿态偏差,在结合常规特征点、特征面检校方法基础上,本文提出了一种带有误差改正数的位置和姿态检校方法。利用TLS获取的车载系统整体点云模型和传感器固有几何属性,获取传感器之间相对关系初值,在此基础上引入误差改正数,构建误差改正模型。在与IGS站联测的检校场中借助平面、球形标靶和平面反射标志等特征,采用最小二乘法迭代法计算误差改正数最优解,从而实现传感器快速检校。试验结果表明,该方法切实可行,检校后点云平面绝对精度和高程绝对精度分别为0.043、0.072 m,相对精度为0.018 m,满足移动测量系统数据获取的精度要求,对促进车载移动测量技术发展和应用具有重要意义。

关键词: 车载移动测量系统, 检校, 初值获取, 误差改正, 全球坐标, 精度评定

Abstract: Aiming at the position and attitude deviations between the laser scanner and the carrier coordinate system in the vehicle-mounted mobile measurement system, a position and attitude calibration method with error correction numbers is proposed based on the combination of conventional feature points and feature surface calibration methods. Use TLS to obtain the overall point cloud model of the vehicle system and the sensor’s inherent geometric properties to obtain the initial value of the relative relationship between the sensors. Based on this, an error correction number is introduced to construct the error correction model. Spherical target and plane reflection mark, the least square method iterative method is used to calculate the optimal solution of the error correction number, so as to achieve rapid sensor calibration. The experimental results show that the method is feasible. After calibration, the absolute accuracy of the point cloud plane and absolute elevation are 0.043 m and 0.072 m, respectively, and the relative accuracy is 0.018 m, which meets the accuracy requirements for data acquisition of mobile measurement systems. Development and application are of great significance.

Key words: vehicle mobile mapping system, calibration, initial value acquisition, error correction, global coordinates, accuracy assessment

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