Least Squares Collocation alternative to Helmert’s transformation with Hausbrandt’s post – transformation correction

Marcin Ligas, Piotr Banasik


The paper presents a least squares collocation - based alternative to Helmert’s transformation with Hausbrandt’s post – transformation correction. The least squares collocation is used as an exact predictor i.e. it honors the data, thus the problem of zero residuals on transformation control points is overcome and zero residuals are assured by the method applied. Despite the fact that the procedure is presented for Helmert’s transformation it may easily be copied to any other form of coordinate transformation. A numerical example is provided within the content of the paper.


least squares collocation; Helmert’s transformation; covariance function; post – transformation correction

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DOI: http://dx.doi.org/10.2478/rgg-2014-0009


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