Research On Retrieving Tide Level And Snow Depth Using GNSS-Reflected Signal

With the deepening of the research on GNSS reflected signals,its inversion theory for surface parameters such as tide level and snow depth has gradually developed and matured.In this paper,the multi-system multi-frequency SNR data in the GNSS reflected signal is used to invert the tide level and snow depth based on the GNSS-IR technology.The specific research contents of this paper are as follows:(1)Taking the tidal level inversion results of MAYG station in 2021 as an example,the inversion accuracy of different types of SNRs in the four major navigation systems is analyzed,and a method of combining the inversion results of each system according to the accuracy of different types of SNRs is proposed.Compared with the single navigation system inversion,the time resolution of this method is greatly improved,and the redundant data in the inversion results can be effectively reduced.(2)In this paper,Kalman filtering is proposed to fuse multi-system and multi-frequency data for tide level inversion data,and a method to accurately determine state noise covariance and observation noise covariance is given.After the fusion,the tidal level inversion accuracy in January 2021 is increased by 26.20%,and the tidal level inversion accuracy for the whole year of 2021 is increased by 26.35%.In order to prove the feasibility and universality of this method,observation data of MAYG station from 2017 to 2020 were used to verify this method,and the inversion accuracy increased by 14.78%,13.10%,22.08%and 16.52%respectively in four years.In the absence of current year tide gauge data,this paper verifies the feasibility of using 2019 inversion results and tide survey data for 2020 data fusion,and the inversion accuracy is improved by 13.55%after fusion.(3)Based on the observation data of SG27 station,the snow depth inversion is studied,and the inversion accuracy of different types of SNR in the four major navigation systems is analyzed.The DBSCAN cluster analysis algorithm was introduced to correct the inversion errors caused by terrain factors.The algorithm had the best correction effect on the GPS system,and the inversion accuracy was improved by up to 34.78%.(4)On the basis of DBSCAN cluster analysis,Kalman filter is used to correct the error of snow depth inversion time series.This method has improved the inversion accuracy of each type of signal-to-noise ratio of the four major navigation systems,especially the inversion accuracy of GLONASS and BDS systems.The degree of error correction is up to 17.95%higher than that using only the DBSCAN cluster analysis algorithm.