Geometric Targets for UAS Lidar
Geometric Targets for UAS Lidar
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DOI：
10.3390/rs11243019
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发表时间：
2019-12-02
期刊：
影响因子：
5
通讯作者：
Grimes, Nathan
中科院分区：
文献类型：
--
作者：
Wilkinson, Benjamin;Lassiter, H. Andrew;Grimes, Nathan
小型无人空中系统（UAS）的激光雷达是收集与各种应用相关的地理空间数据的可行方法。来自UAS激光雷达的点云需要一种精度评估、校准和调整的方法。为了执行这些程序，必须精确地找到点云内的特定位置。为了做到这一点，人工目标可以用于农村环境，或者在场景中缺乏可识别和可测量特征的任何地方。提出了一种基于几何结构的精确定位激光雷达目标设计方法。在两种场景下测试了目标和相关的测量算法，以研究它们在不同点密度和不同算法严格程度下的性能。结果表明，从典型扫描参数到< 2 cm sigma范围内的目标均能准确定位，在基于传播点位置不确定性的算法中加入观测权重可提高定位精度。
Lidar from small unoccupied aerial systems (UAS) is a viable method for collecting geospatial data associated with a wide variety of applications. Point clouds from UAS lidar require a means for accuracy assessment, calibration, and adjustment. In order to carry out these procedures, specific locations within the point cloud must be precisely found. To do this, artificial targets may be used for rural settings, or anywhere there is a lack of identifiable and measurable features in the scene. This paper presents the design of lidar targets for precise location based on geometric structure. The targets and associated mensuration algorithm were tested in two scenarios to investigate their performance under different point densities, and different levels of algorithmic rigor. The results show that the targets can be accurately located within point clouds from typical scanning parameters to < 2 cm sigma, and that including observation weights in the algorithm based on propagated point position uncertainty leads to more accurate results.