Evaluation and combination of quad-constellation multi-GNSS multipath reflectometry applied to sea level retrieval

Abstract

The satellites of the Global Navigation Satellite System (GNSS) continuously broadcast L-band signals at about a 20-cm wavelength. Some signal-to-noise ratio (SNR) data received by off-shelf geodetic antennas contain the multipath information of the sea, and they have been demonstrated for use in retrieving sea levels; however, compared with conventional tide gauges, this GNSS multipath reflectometry (GNSS-MR) technique is limited in terms of both precision and sampling rate. The simplest measure to increase the sampling rate of retrievals is to use SNR data from more satellite tracks at more satellite constellations. This study estimated the sea level of station BRST belonging to the Multi-GNSS Experiment (MGEX) using SNR data of four constellations (GPS, GLONASS, Galileo, and BeiDou) of the GNSS. It was found that the S5X/S2X, S2P/S2C, S5X, and S7I SNR types had optimal precisions for the GPS, GLONASS, Galileo, and BeiDou, respectively. In addition, we developed a multi-GNSS combination algorithm to formulate a 10-min sea level time series based on a state transition equation set and a robust regression solution strategy. The combined sea level retrieval time series had an approximately 40%–75% accuracy improvement compared to individual signal sea level retrievals; with a constant sampling interval in the 10 min window, the combined method presented here is beneficial for both the precision and sampling rate. This approach is novel and advanced in two key ways, in that we use data from four constellations simultaneously and through the regression strategy, which is applied to synthesize all data into a time series at regular 10-min intervals. This technique could be applied to other sites and is therefore beneficial for the GNSS-MR community.