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

机译:现有铁路勘测中高精度车载激光雷达点云数据采集方法研究

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摘要

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.
机译:现有的铁路勘测是掌握铁路情况和监测铁路运行安全的必要措施。与现有的传统铁路勘测技术相比,采用非接触式测量方法获得沿线的三维信息是一个非常重要的研究课题。车载激光雷达技术在铁路上的应用可以有效地解决这一问题。然而,由于地形复杂以及铁路沿线的电子和电磁设备无法满足现有铁路测量的要求,因此车载LiDAR点云数据的准确性会受到影响,我们提出了一种新颖的方法通过部署反射目标提高点云的准确性。通过现场实验验证了该方法,并对实验数据进行了精确分析。结果表明,该方法能够满足现有铁路勘测的要求,提高了LiDAR数据采集的效率和准确性,增强了在复杂环境下的工作能力。最后,对论文的研究工作进行了总结,并对存在的问题进行了展望。

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  • 会议地点 Fort Worth(US)
  • 作者单位

    State Key Laboratory of Rail Transit Engineering Informatization(FSDI) No.2 Xiying Road Yanta District Xi'an Shanxi Province China 710043;

    Institute of Remote Sensing and GIS Peking University No.5 Yiheyuan Road Haidian District Beijing China 100871;

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    Indexes;

    机译:指标;

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