Processing of multi-GNSS constellations based on raw observations

Sebastian Strasser, Torsten Mayer-Gürr

Research output: Contribution to conferenceAbstract


With the modernization of GPS and GLONASS and the advent of Galileo, BeiDou, and regional satellite systems,there is now a multitude of signals available for ground station networks to observe. As a result, the complexityof deriving GNSS products like satellite orbits, clocks, station positions, and signal biases increases significantlywhen dealing with all these signals at once. The raw observation approach was developed to cope with this in-creased complexity in multi-GNSS processing. It is based on undifferenced and uncombined observations andtherefore allows full exploitation of the information contained in each individual observable and preserves theoriginal measurement accuracy. While the approach was developed with the aim of multi-GNSS processing, it wasinitially tested and evaluated using only the GPS constellation to limit the complexity of the software implemen-tation. It is now being expanded to full multi-GNSS processing, the details of which will be the main topic of thissubmission. One focus lies on how inter-frequency and inter-system signal biases are handled during processing.The time-variability of those and related parameters and possible modeling strategies will be investigated, e.g. bymodeling clocks and biases as stochastic processes. The resulting multi-GNSS products are compared with thoseof the IGS MGEX analysis centers to evaluate the performance of the raw observation approach.


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