Analysis and combination of multi-GNSS snow depth retrievals in multipath reflectometry

Abstract

The Global Navigation Satellite Systems (GNSS) continuously broadcast radio signals at two or more frequencies in the L-band, providing extensive data for GNSS multipath reflectometry. Multi-GNSS constellations provide more signals and more tracks than individual constellations, achieving greater azimuthal coverage and more frequent retrievals. The main aim of this study is to retrieve snow depth using multi-GNSS data, analyze the multi-GNSS retrievals, and then combine them. Data of four constellations from three GNSS sites are analyzed, including the BeiDou and Galileo signals, which are rarely used to retrieve snow depth. The snow depth retrievals are estimated for signal-to-noise ratio data of each signal at first. The retrievals of individual signals from four constellations, except that of the GPS P-code signal, have no detectable inter-signal bias, thus showing the same trend describing snow depth variation. Then a multi-GNSS combination method based on robust regression is used to combine the inter-constellation inter-signal retrievals, and the multi-GNSS combined retrievals show an improvement in precision, availability, and temporal sampling. Compared to that of individual signals, it achieves about 50% improvement in precision, a smaller uncertainty, and a constant sampling interval of 6 h.