PPP ANALISYS WITH GPS AND GLONASS INTEGRATION IN PERIODS UNDER IONOSPHERIC SCINTILLATION EFFECTS

Abstract:

The GNSS is widely used nowadays either for geodetic positioning or scientific purposes. The GNSS currently includes GPS, GLONASS, Galileo among other emerging systems. The GPS and GLONASS are currently operational with a full satellite constellation. The GPS is still the most used nowadays and both GPS and GLONASS are under a modernization process. The geodetic positioning by using data from multi-constellation can provide better accuracy in positioning and also more reliability. The PPP is benefited once the satellite geometry is crucial in this method, mainly for kinematic scenarios. The satellite geometry can change suddenly for data collected in urban areas or in conditions of strong atmospheric effects such as Ionospheric Scintillation (IS) that causes weakening of signals with cycle slips and even loss of lock. The IS is caused by small irregularities in the ionosphere layer and is characterized by rapid change in amplitude and phase of the signal being stronger in equatorial and high latitudes regions. In this work the PPP is evaluated with GPS and GLONASS data collected by monitoring receivers from Brazilian CIGALA/CALIBRA network under IS conditions. The PPP processing was accomplished by using the GPSPPP software provided by Natural Resources Canadian (NRCAN). The IS effects were analyzed taking account the S4 and PHI60 indices. Considering periods with moderate IS effects, the use of only GPS data in the PPP presented several peaks in the coordinate time series due to cycle slips and loos of lock. In cycle slip conditions the ambiguity parameter are reinitialized by GPSPPP and considering loss of lock few satellites can be available in some epochs affecting the positioning geometry and consequently decreasing accuracy. In such situations, the PPP using GPS and GLONASS data presented improvements in positioning accuracy of the order to 70% in height component when compared with PPP using only GPS data. Analyses of GDOP and ambiguities parameters were also performed.