首页|Processing TLS heterogeneous data by applying robust Msplit estimation
Processing TLS heterogeneous data by applying robust Msplit estimation
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NSTL
Elsevier
? 2022 The Author(s)Terrestrial laser scanning provides a point cloud containing hundreds or thousands of points. One should suppose that some points are mismeasured; hence, the observation set is not homogeneous, requiring the application of modern statistical methods, such as Msplit estimation. That novel method is designed for processing observation sets that are unrecognized mixtures of realizations of at least two random variables (however, a priori, there is no information on subset division). The basic Msplit estimates are not robust against outlying observations. The paper proposes new variants of Msplit estimation designed as robust against outliers. The example applications prove that the new variants are twice as accurate as of the existing Msplit estimates or four times more accurate than the conventional robust assessments. What is more, new variants can provide acceptable results even if the share of outliers exceeds 50%, which is impossible for traditional robust methods.
Estimation theoryMsplit estimationRobustness against outliersTerrestrial laser scanning
Wyszkowska P.、Duchnowski R.
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Department of Geodesy Institute of Geodesy and Civil Engineering Faculty of Geoengineering University of Warmia and Mazury in Olsztyn
NSTL
Elsevier
