2017
DOI: 10.1515/jogs-2017-0012
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A weighted adjustment of a similarity transformation between two point sets containing errors

Abstract: Abstract:For an adjustment of a similarity transformation, it is often appropriate to consider that both the source and the target coordinates of the transformation are affected by errors. For the least squares adjustment of this problem, a direct solution is possible in the cases of speci c weighing schemas of the coordinates. Such a problem is considered in the present contribution and a direct solution is generally derived for the m-dimensional space. The applied weighing schema allows (fully populated) poi… Show more

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Cited by 9 publications
(5 citation statements)
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“…To estimate the rotational component, the authors suggest an orthonormal matrix decomposition, maximizing the similarity between transformed correspondences. An analytical and robust approach using a weighted Least-Squares was presented by Marx [11] to mitigate the influence of false correspondences on the final result.…”
Section: B Odometry Estimationmentioning
confidence: 99%
“…To estimate the rotational component, the authors suggest an orthonormal matrix decomposition, maximizing the similarity between transformed correspondences. An analytical and robust approach using a weighted Least-Squares was presented by Marx [11] to mitigate the influence of false correspondences on the final result.…”
Section: B Odometry Estimationmentioning
confidence: 99%
“…In addition, the properties of this method have also been analysed in the literature, e.g., [19][20][21][22]. Various authors have also studied related issues, including similarity transformation problems under the GHM, proposed alternative solutions [23,24], and compared with other similar approaches, e.g., Gauss-Newton [25]. Also, some more advanced topics, including the GHM with a singular dispersion matrix [26], parameter estimation within the GHM using the Pareto optimality [27] or robust parameter estimation of the non-linear GHM [28], have been investigated.…”
Section: Introductionmentioning
confidence: 99%
“…So far, a large number of algorithms of three-dimensional coordinate transformation have been presented (cf., e.g., Aydin et al 2018;Grafarend and Awange 2003;Kanatani and Niitsuma 2012;Kurt 2018;Ligas and Prochniewicz 2019;Mahboub 2016;Marx 2017;Mercan et al 2018;Mihajlović and Cvijetinović 2017;Păun et al 2017;Shen et al 2006;Uygur et al 2020;Walker et al 1991;Wang et al 2014;Zeng 2015;Yi 2010, 2011;Zeng et al 2016Zeng et al , 2018Zeng et al , 2019. They can be classified into iterative algorithm or analytical algorithm.…”
Section: Introductionmentioning
confidence: 99%