Biased and unbiased estimates based on laser scans of surfaces with unknown deformations
Biased and unbiased estimates based on laser scans of surfaces with unknown deformations
Dokument öffnen (16MB)Datum der Veröffentlichung
02.10.2014Verlag / herausgebende Einrichtung
de GruyterVerlagsort
BerlinMetadaten
Zur Langanzeige
Zitierbarer Link (Handle URI) 
https://hdl.handle.net/20.500.11811/8364
Inhalt
The estimates based on laser scans of surfaces with unknown deformations are biased and not reproducible when changing the scanning geometry. While the existence of a bias is only disadvantageous at some applications, non-reproducible estimates are never desired. Hence, this varying bias and its origin need to be investigated – since this situation has not been examined sufficiently in the literature. Analyzing this situation, the dependence of the estimation on the network configuration is highlighted: the network configuration – studied similarly to geodetic networks – rules about the impact of the deformation.
As pointed out, this impact can be altered by manipulating the network configuration. Therefore, several strategies are proposed. These include manipulations of the least-squares adjustment as well as robust estimation. It is revealed that the reproducibility of the estimates can indeed be significantly increased by some of the proposed least-squares manipulations. However, the bias can only be significantly reduced by robust estimation.
As pointed out, this impact can be altered by manipulating the network configuration. Therefore, several strategies are proposed. These include manipulations of the least-squares adjustment as well as robust estimation. It is revealed that the reproducibility of the estimates can indeed be significantly increased by some of the proposed least-squares manipulations. However, the bias can only be significantly reduced by robust estimation.
Schlagwörter
laser scanning, deformation, surface approximation, bias, network con guration, partial redundancies
Klassifikation (DDC)
526.1 GeodäsieErschienen in
Journal of Applied Geodesy, 8, 3, S. 169-183Erstpublikation
https://doi.org/10.1515/jag-2014-0006Holst, Christoph; Artz, Thomas; Kuhlmann, Heiner: Biased and unbiased estimates based on laser scans of surfaces with unknown deformations. In: Journal of Applied Geodesy. 8, 3, 169-183.
Online-Ausgabe in bonndoc: https://hdl.handle.net/20.500.11811/8364
Online-Ausgabe in bonndoc: https://hdl.handle.net/20.500.11811/8364
@article{handle:20.500.11811/8364,
author = {{Christoph Holst} and {Thomas Artz} and {Heiner Kuhlmann}},
title = {Biased and unbiased estimates based on laser scans of surfaces with unknown deformations},
publisher = {de Gruyter},
year = 2014,
month = oct,
journal = {Journal of Applied Geodesy},
volume = 8,
number = 3,
pages = 169--183,
note = {The estimates based on laser scans of surfaces with unknown deformations are biased and not reproducible when changing the scanning geometry. While the existence of a bias is only disadvantageous at some applications, non-reproducible estimates are never desired. Hence, this varying bias and its origin need to be investigated – since this situation has not been examined sufficiently in the literature. Analyzing this situation, the dependence of the estimation on the network configuration is highlighted: the network configuration – studied similarly to geodetic networks – rules about the impact of the deformation.
As pointed out, this impact can be altered by manipulating the network configuration. Therefore, several strategies are proposed. These include manipulations of the least-squares adjustment as well as robust estimation. It is revealed that the reproducibility of the estimates can indeed be significantly increased by some of the proposed least-squares manipulations. However, the bias can only be significantly reduced by robust estimation.},
url = {https://hdl.handle.net/20.500.11811/8364}
}
author = {{Christoph Holst} and {Thomas Artz} and {Heiner Kuhlmann}},
title = {Biased and unbiased estimates based on laser scans of surfaces with unknown deformations},
publisher = {de Gruyter},
year = 2014,
month = oct,
journal = {Journal of Applied Geodesy},
volume = 8,
number = 3,
pages = 169--183,
note = {The estimates based on laser scans of surfaces with unknown deformations are biased and not reproducible when changing the scanning geometry. While the existence of a bias is only disadvantageous at some applications, non-reproducible estimates are never desired. Hence, this varying bias and its origin need to be investigated – since this situation has not been examined sufficiently in the literature. Analyzing this situation, the dependence of the estimation on the network configuration is highlighted: the network configuration – studied similarly to geodetic networks – rules about the impact of the deformation.
As pointed out, this impact can be altered by manipulating the network configuration. Therefore, several strategies are proposed. These include manipulations of the least-squares adjustment as well as robust estimation. It is revealed that the reproducibility of the estimates can indeed be significantly increased by some of the proposed least-squares manipulations. However, the bias can only be significantly reduced by robust estimation.},
url = {https://hdl.handle.net/20.500.11811/8364}
}
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