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On the Statistical Tests Over Fennoscandian GNSS/levelling Networks (Civil Project)

In Geodesy and Surveying we work with a large amount of observations which always contains different types of errors. The errors decrease the quality of the observations and propagate to the results. Therefore, detection and removing the gross errors are of vital importance.

The Global Navigation Satellite Systems (GNSS) can be used to measure the ellipsoidal height and by subtracting an existing geoid height from that, the orthometric height can be determined. There is a simple linear relation amongst these triple heights, which cannot be fulfilled due to the presence of different types of error. One of the important sort of these errors is gross errors.

This study concerns about investigation and detection of blunders or gross errors on the 4346GNSS/levelling points over Fennoscandia. Each country has its own data set with specific precision. The well-known gravity model EGM08 is used to compute the geoid heights with respect to WGS84 reference ellipsoid. We have a large amount of data and we expect that their errors follow the normal distribution. The main aim of this thesis is to apply some data screening methods both before and after adjustment process in such a way that the normal distribution of the data set is achieved by eliminating the erroneous data.

This will be done by performing the pre- and post-adjustment data screening. For the pre-adjustment we performed data filtering, test of normality of observations and test of their variances for the GNSS/levelling data over Sweden, Denmark, Norway and Finland. We used the 4-, 5- and 7-parameter corrective surfaces for modelling the systematic trends of the differences betweenthe EGM08 geoid model and the ellipsoidal and orthometric height differences.

The test of normality of residuals, global test of variance, Baarda’s data snooping and Tau test will beperformed after the removal of the trends. Numerical studies show that the GNSS/levelling data of Sweden, Denmark and Finland are of good qualities, but the claimed errors for the data are rather optimistic. The situation was complicated for the data of Norway and we could not see the normality of the data and even the claimed accuracies seem to be optimistic.
Source: KTH
Author: Zoghi, Sedigheh

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