Comparing GPS positioning errors derived from GAMIT/GLOBK and Bernese GNSS software packages: A case study in CORS-TR in Turkey

摘要

Global Navigation Satellite System (GNSS) processing software packages such as GAMIT/GLOBK, Bernese, GIPSY/OASIS etc., have an important role in high-precision GNSS studies. For a single GNSS session, they result in Formal Error (FE) rather than positioning accuracy because it may not be possible to incorporate the correlations in the GNSS data properly into the stochastic model of the estimation procedure. Therefore, a GNSS network used for high-precision studies should be measured repeatedly in different sequential days to have repeatabilities of positions to be used for representing the RMS errors of positioning. This contribution investigates the relationship between the FE and RMS error of Global Positioning System (GPS) positioning for GAMIT/GLOBK (V10.6) and Bernese (V5.2) software packages. For this purpose, seven days of GPS observations in six different sub-networks consisting of totally 36 Continuously Operating Reference Station (CORS) network stations in Turkey are used. The sub-networks were selected such that they were distributed homogenously throughout Turkey. The GPS observations were processed in the ITRF2008 reference frame using both GAMIT/GLOBK and Bernese software packages. Daily repeatabilities of North, East and Up coordinates of each station obtained from two software packages are nearly the same. However, their FEs are very different. GAMIT/GLOBK gives bigger FEs while Bernese results in too smaller FEs compared to their RMS errors of positioning. A linear relationship exists between the average of seven days FEs and the RMS errors for both software packages. This relationship is defined as the 'Scale Factor (SF) = RMS/FE'. It is shown that a unique SF for the corresponding software package can be given as the mean value of the SFs associated with all points used in the study. According to our analysis, the mean SF in the region is 0.38 and 3.82 for GAMIT/GLOBK and Bernese, respectively.