基于GNSS-IR双系统组合的土壤湿度多星线性回归反演模型

提出一种GPS/BDS双系统组合的土壤湿度多星线性回归反演模型，并以GNSS接收机实测数据为例，对比分析不同GPS和BDS卫星组合反演土壤湿度的效果。实验表明：1)GPS和BDS双系统组合相对于单系统在短观测时间内可以提高有效卫星数，通过多元线性回归原理可实现双系统多卫星的有效融合，提高土壤湿度反演的精度；2)当GPS和BDS组合卫星数达到6颗以上时，反演效果趋于稳定，反演结果与土壤湿度的相关系数均优于0.90，RMSE相对于单星至少提高25.8%。

Multi-Satellite Linear Regression Inversion Model for Soil Moisture Based on GNSS-IR Dual-System Combination

We propose a multi-satellite linear regression inversion model of soil moisture with GPS/BDS dual-system combination. Taking the measured data from GNSS receivers as an example, we compare and analyze the effect of different GPS and BDS satellite combinations for inversion soil moisture. The experiments show that: 1) The combination of GPS and BDS dual-system can increase the number of effective satellites in the short observation time compared to the single-system. The multiple linear regression principle can achieve the effective fusion for dual-system satellites, which can improve the accuracy of soil moisture inversion. 2) When the combined number of GPS and BDS satellites reaches 6 or more, the inversion effect tends to be stable, and the correlation coefficients of their inversion results and soil moisture are all greater than 0.90, and the RMSE is improved by at least 25.8% compared with that of single satellite.