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Open Access Published by De Gruyter Open Access April 30, 2013

Closed-form and iterative weighted least squares solutions of Helmert transformation parameters

  • L.E. Sjöberg

Abstract

The Helmert transformation is the most common transformation between different geodetic systems. In 2-D, in contrast to higher dimensions, it is a well-known procedure how to determine the 4 transformation parameters in a closed form. Here we derive the closed-form weighted least squares solution in m-dimensional space for an arbitrary number (≥ m) of coordinate set-ups in two related systems. The solution employs singular value decomposition (SVD) for the rotation matrix, while the translation vector and scale parameters are obtained in simpler ways. To avoid the SVD routine, we also present an iterative approach to solve for the rotation matrix. The paper is completed with a test procedure for detecting outlying coordinate pairs.

References

Awange J.L., Grafarend E.W., Paláncz B. and Zaletnyik P., 2010, Algebraic Geodesy and Geoinformatics, 2nd ed., Springer Verlag, Berlin Heidelberg10.1007/978-3-642-12124-1Search in Google Scholar

Bjerhammar A., 1973, Theory of errors and generalized matrix inverses, Elsevier Publ. Co., Amsterdam and New York.Search in Google Scholar

Crosilla F., 2003, Procrustes analysis and geodetic science. In: Grafarend, E. W., Krumm, F. W., Schwarze, V. S. (Eds.), 2003, Geodesy - The Challenge of the Third Millenium, Springer, pp. 287-29210.1007/978-3-662-05296-9_29Search in Google Scholar

Grafarend E. W. and Awange J. L., 2003, Nonlinear analysis of the three-dimensional datum transformation conformal group C7 (3), J Geod. 77, 66-7610.1007/s00190-002-0299-9Search in Google Scholar

Helmert F.R., 1924, Ausgleichungsrechnung nach der Methode der kleinsten Quadrate mit Anwendungen auf die Geodäsie, die Physik und die Theorie der Messinstrumente, 3rd edition, Leipzig and BerlinSearch in Google Scholar

Horn B. K. P., 1987, Closed-form solution of absolute orientation using orthonormal matrices, J. Opt. Soc. Amer. A, 5, 7, 1127-113510.1364/JOSAA.5.001127Search in Google Scholar

Lissitz, R. W., Schönemann P. H. and Lingoes J. C., 1976, A solution to the weighted Procrustes problem in which the transformation is in agreement with the loss function. Psychometrika 41, 4, 547-55010.1007/BF02296976Search in Google Scholar

Myronenko A. and Song X., 2009, On the closed-form solution of the rotation matrix arising in computer vision problems, arXiv:0904.1613v1 [cs.CV]Search in Google Scholar

Schönemann P. H., 1966, Generalised solution of the orthogonal Procrustes problem, Psychometrika 31, 1-1010.1007/BF02289451Search in Google Scholar

Schönemann P. H. and Carroll R. M., 1970, On fitting one matrix to another under choice of a central dilation and a rigid motion. Psychometrika 35, 245-25510.1007/BF02291266Search in Google Scholar

Späth H., 2003, Identifying spatial point sets, Math. Com. 8, 69-75Search in Google Scholar

Späth H., 2004, A numerical method for determining the spatial Helmert transformation in case of different scale factors, Zeitschr. f. Verm. 129, 255-259Search in Google Scholar

Umeyama S., 1991, Least-squares estimation of transformation parameters between two point patterns, IEEE Transactions on pattern analysis and machine intelligence, 13, 4, 376-38010.1109/34.88573Search in Google Scholar

Watson G. A., 2006, Computing Helmert transformations, J. Comp. and Appl. Maths. 197, 2, 387-394 10.1016/j.cam.2005.06.047Search in Google Scholar

Published Online: 2013-04-30
Published in Print: 2013-03-1

This content is open access.

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