Investigation of the reliability of the different approaches for using the robust estimation methods in deformation analysis

Deformation analysis is one of the most important subjects in Geomatic Engineering. It classically depends on the comparison of the coordinates’ differences estimated in different periods. If the coordinate differences are statistically proved as significant, they are interpreted as displacement. In literature there are different deformation analysis models. As well as conventional deformation analysis (CDA) models, similarity (Helmert) transformation is one of these models used for deformation analysis. In similarity transformation, the residuals to be estimated from similarity transformation can be used in deformation analysis. By investigating the residuals estimated from both conventional and robust methods, it can be determined whether the point has displaced or not. Deformation analysis methods do not provide correct and the same results in all conditions. The successes of the methods change depending on the sample dataset used, the number of the displaced points in the network and the magnitude of the displacement. One of the methods used for measuring the reliability of the analysis methods is the Mean Success Rate (MSR). In this study, a horizontal control network has been simulated as two periods. Since only the random errors are considered in the first period measurements, for the second period measurements, both random errors and magnitudes of the displacements are taken into consideration. Each of these periods forms one working sample. The usability of the robust methods in deformation analysis for two different approaches has been investigated by using this working samples. In the first approach, the displaced points have been identified by applying the significance test to the residuals estimated by robust methods in similarity transformation. In the second approach, the displaced points have been detected by applying the outlier detection strategy to the same residuals. In this study, 10 000 working samples have been formed. The results of both approaches have been compared with the results of the CDA methods. According to the results obtained, although both CDA and robust methods have similar results for one displaced point, in the case of more than one displaced point CDA has more reliable results than robust methods. Also, when the number of the displaced points increase, the MSRs of the methods decrease. Contrary to this, if the magnitudes of the displacements increase, the MSRs of the methods increase