| 多系统融合精密单点定位在机载雷达电力线巡检中的应用 |
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| 引用本文： | 孟昊,韩保民,王胜利,王进.多系统融合精密单点定位在机载雷达电力线巡检中的应用[J].全球定位系统,2021,46(5):104-110. |
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| 作者姓名： | 孟昊 韩保民 王胜利 王进 |
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| 作者单位： | 1.山东理工 大学 建筑工程学院，山东 淄博 255000 |
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| 基金项目： | 国家自然科学基金（41074001） |
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| 摘 要： | 通过无人机搭载激光雷达(LiDAR)测量系统进行电力线巡检实验，提出了一种基于多系统精密单点定位(PPP)的机载LiDAR电力线巡检方法，重点分析了基站差分、单系统PPP、多系统融合PPP三种处理策略生成POS数据的方法，并利用江苏省中北部采集的机载雷达数据及人工布设的控制点结果进行验证. 实验结果表明:三种方法得到的POS数据均方根误差(RMSE)均在0.016 m以内，与单系统PPP相比，多系统PPP在高程方向提高了12%，在东(E)方向提高了21%，在北(N)方向提高了17%，文中提出的方法生成三维(3D)点云数据精度较高，生成的点云数据精度满足精细电力线巡检的要求.
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| 关 键 词： | 精密单点定位(PPP) 机载激光雷达(LiDAR) 电力线巡检 多源数据融合 点云数据精度 |
| 收稿时间： | 2021-04-27 |
Airborne radar power line inspection based on multi-GNSS fusion precise single point positioning |
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| Institution: | 1.School of Civil and Architectural Engineering, Shandong University of technology, Zibo 255000, China2.College of Ocean Science and Engineering, Shandong University of science and technology, Qingdao 266590, China3.College of Geodesy and Geomatics, Shandong University of science and technology, Qingdao 266590, China |
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| Abstract: | Through the power line inspection experiment of UAV equipped with light detection and ranging (LiDAR) measurement system, this paper proposes an airborne LiDAR power line inspection method based on multi-system precise single-point positioning. The article focuses on the analysis of the three processing strategies of base station differential, single-system precision single point positioning (PPP), and multi-system fusion PPP to generate POS data. The airborne LiDAR data are collected in the north-central part of Jiangsu Province and the results of manually placed control points for verification. The experimental results show that the root mean square error of the POS data obtained by the three methods are all within 0.016 m. Compared with the single-system PPP, the multi-system precision single-point positioning increases by 12% in the elevation direction and 21% in the east (E) direction. The north (N) direction has increased by 17%. The method proposed in this paper has high accuracy in generating three dimensional (3D) point cloud data, and the accuracy of the generated point cloud data meets the requirements of fine power line inspection. |
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