Study on the method of high-precision vehicle-borne lidar point clouds data acquisition in existing railway survey

• Published in: 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS) pp. 1704 - 1707
• Main Authors: Wei Li, Xiaochun Ren, Fei Li, Wei Wang
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.07.2017
• Subjects: existing railway survey; Indexes; point cloud; reflective target; vehicle-borne LiDAR
• ISSN: 2153-7003
• DOI: 10.1109/IGARSS.2017.8127302

The existing railway survey is a necessary measure to master the railway situation and monitor the safety of railway operation. Compared with the existing traditional railway survey technology, using the method of non-contact measurement to obtain the line three-dimensional information along the line is a very important research topic. The application of vehicle-borne LiDAR technology in railway can effectively solve the problem. However, the accuracy of the vehicle-borne LiDAR point cloud data will be affected due to complex terrain and the electronic and electromagnetic equipment along the railway line which cannot support the requirements of the existing railway survey in this paper, we propose a novel approach to improve the accuracy of point cloud by deploying the reflective target. The method is verified by field experiment and precision analysis is performed for the experimental data. The results suggest that with the method, vehicle-borne LiDAR can meet the requirements of the existing railway survey, improve the efficiency and accuracy of collecting LiDAR data, enhance the ability to work in complex environments. Finally, research work of the paper is summarized and the prospect of the problems is presented.