Snow Depth Retrieval With Multiazimuth and Multisatellite Data Fusion of GNSS-IR Considering the Influence of Surface Fluctuation.

Utilizing global navigation satellite system interferometric reflectometry (GNSS-IR) technology to obtain snow depth (SD) has the advantages of all-day, low cost, and large amount of available data. At present, there is still a lack of in-depth research on the influence of weak surface fluctuation on SD inversion. In this article, we investigate the influence of surface fluctuation on GNSS-IR SD retrieval by analyzing variation of reflection height in different azimuths through clustering based on different satellites during snow-free period, and the surface correction value of each cluster is obtained to correct SD in snowy period; the most probable value of daily SD is obtained by multiazimuth and multisatellite SD fusion. In order to prove the rationality and effectiveness of the proposed method, the data of two GNSS observation stations (AB33 and P351) with different elevations and different SDs from the plate boundary observation (PBO) are used to carry out experiments. The results show that the SD accuracy with multiazimuth SD fusion after surface correction is improved significantly. The correlation coefficient ( $R$ ) increased by 5.04%, the root-mean-square error (RMSE) decreased by 43.49%, and the mean absolute error (MAE) decreased by 47.62%. In addition, the average $R$ , RMSE, and MAE of multisatellite SD fusion results are 0.99, 0.02 m, and 0.01 m, respectively. The mean error (ME) of the two fusion methods is also significantly reduced. The study provides insightful new ideas for inverting SD using GNSS reflection signals.