Abstract：We adopt the function model with damping factor and use the genetic algorithm(GA) assisted nonlinear least squares(NLS) to solve the phase parameters. The results show that:1) Compared with the standard cosine function model, the correlation coefficient between the inversion phase and soil moisture is significantly improved, and the inversion results are more stable. In the three elevation angle ranges of 5°-15°, 5°-20°, and 5°-25°, the correlation coefficients can all be greater than 0.68. The difference between the correlation coefficients of different elevation angles is less than 0.07. 2) The inversion accuracy has been improved to varying degrees, with R2 increased by 5.72%-76.06%, RMSE decreased by 6.12%-24.24%, MAE decreased by 2.7%-28.3%. By applying the inversion results of this method in multi-satellite linear regression model, the average RMSE decreased by 10%.
