Spatio-temporal filtering for determination ofcommon mode error in regional GNSS networks

Abstract

Abstract The spatial correlation between different stationsfor individual components in the regional GNSS networksseems to be significant. The mismodelling in satelliteorbits, the Earth orientation parameters (EOP), largescaleatmospheric effects or satellite antenna phase centrecorrections can all cause the regionally correlated errors.This kind of GPS time series errors are referred to ascommon mode errors (CMEs). They are usually estimatedwith the regional spatial filtering, such as the "stacking".In this paper, we show the stacking approach for the setof ASG-EUPOS permanent stations, assuming that spatialdistribution of the CME is uniform over the whole regionof Poland (more than 600 km extent). The ASG-EUPOSis a multifunctional precise positioning system based onthe reference network designed for Poland. We used a 5-year span time series (2008-2012) of daily solutions in theITRF2008 from Bernese 5.0 processed by the Military Universityof Technology EPN Local Analysis Centre (MUTLAC). At the beginning of our analyses concerning spatialdependencies, the correlation coefficients between eachpair of the stations in the GNSS network were calculated.This analysis shows that spatio-temporal behaviour of theGPS-derived time series is not purely random, but there isthe evident uniform spatial response. In order to quantifythe influence of filtering using CME, the norms L1 and L2were determined. The values of these norms were calculatedfor the North, East and Up components twice: beforeperforming the filtration and after stacking. The observedreduction of the L1 and L2 norms was up to 30% dependingon the dimension of the network. However, the questionhow to define an optimal size of CME-analysed subnetworkremains unanswered in this research, due to thefact that our network is not extended enough.