Semiempirical backscatter models at low incidence angles under rain conditions

Abstract

Rain affects radar backscatter to some extent, and the effect is complicated. Our article models the radar backscatter at low incidence angles under rain conditions by a semiempirical method. Starting from no rain conditions, we choose two optics models as backscatter models at low incidence angles. From the rain effect analysis, an empirical function is deduced by curve fitting. Then we add the empirical function with the backscatter models at low incidence angles under no rain conditions, and two backscatter models at low incidence angles under rain conditions are obtained. After comparing with measured backscatter, we select a quasispecular model combined with the empirical function as a new backscatter model. Further, a correction item is introduced to improve the model accuracy. Results demonstrate that the model can predict backscatter as rain rate ranging from −15 to 5 mm/h dB and wind speed ranging from 6 to 16 m/s with a root-mean-square error of 0.97 dB and a correlation coefficient of 0.81.