Abstract
The article deals with the possibilities of the automatic detection of outliers during the processing of accurate surveying measurements which are assessed by the least squares adjustment. These are classical terrestrial measurements obtained during the survey of high precision spatial geodetic networks. The authors use robust M-estimators for the automatic detection of outlying measurements. Robust adjustment is combined with the method of the assessment adjusted measurements’ residuals. In the article, the authors focus on the description of the detection method and its testing. The testing concept consists in the determination of the efficiency of the detection of outliers of experimental measurements in a model spatial geodetic network. By means of a computer pseudorandom number generator, a model of ideally created measurements is generated in the first phase of experimental testing. This model is repeatedly contaminated with varying numbers of differently outlying measurements, and the automatic detection method is applied during their subsequent processing. The resulting detected measurements are compared against contaminated input outliers and the actual efficiency of the detection method is identified.
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Acknowledgments
The article was written with support from the internal grant of Czech Technical University in Prague: SGS13/059/OHK1/1T/11 “Optimization of acquisition and processing of 3D data for purpose of engineering surveying”.
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Třasák, P., Štroner, M. Outlier detection efficiency in the high precision geodetic network adjustment. Acta Geod Geophys 49, 161–175 (2014). https://doi.org/10.1007/s40328-014-0045-9
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DOI: https://doi.org/10.1007/s40328-014-0045-9