A synthetic covariance matrix for monitoring by terrestrial laser scanning
A synthetic covariance matrix for monitoring by terrestrial laser scanning
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DOI：
10.1515/jag-2016-0026
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发表时间：
2017-01-01
影响因子：
1.4
通讯作者：
Schwieger, Volker
中科院分区：
文献类型：
--
作者：
Kauker, Stephanie;Schwieger, Volker
激光扫描点云内的建模相关性可以通过使用合成协方差矩阵来实现。这些基于基本误差模型，其中包含不同的相关组：非相关、函数相关和随机相关。通过将基本误差模型应用于地面激光扫描，应考虑几组误差源：仪器误差源、大气误差源和基于物体的误差源。本贡献介绍了 Leica HDS 7000 的计算。估计并讨论了确定的方差和点的空间相关性。由此，对于5 m扫描范围，点云的平均标准偏差高达0.6 mm，平均相关性约为0.6。与 Kauker 和 Schwieger [17] 等之前的出版物相比，这些数值的变化主要是由于充分考虑了与对象相关的误差源。
Modelling correlations within laser scanning point clouds can be achieved by using synthetic covariance matrices. These are based on the elementary error model which contains different groups of correlations: non-correlating, functional correlating and stochastic correlating. By applying the elementary error model on terrestrial laser scanning several groups of error sources should be considered: instrumental, atmospheric and object based. This contribution presents calculations for the Leica HDS 7000. The determined variances and the spatial correlations of the points are estimated and discussed. Hereby, the mean standard deviation of the point cloud is up to 0.6 mm and the mean correlation is about 0.6 with respect to 5 m scanning range. The change of these numerical values compared to previous publications as Kauker and Schwieger [17] is mainly caused by the complete consideration of the object related error sources.