Compensation of the Propagation and Clutter Effects of Rainfall for Pol-SAR-Based Sea-Surface Target Detection

Polarimetric synthetic aperture radar (Pol-SAR) is one of the most important approaches for sea-surface target detection, but under rainfall conditions it tends to be distorted by the electromagnetic (EM) propagation effects and clutter interference of rainfall. To address this problem, this paper proposes a joint compensation method to mitigate the impacts of rainfall on the detection of sea-surface targets. In the method, a composite imaging model that thoroughly takes into account the propagation and scattering effects of rainfall, sea surface, and ship targets is first established. Then, a range-wise algorithm is proposed to effectively estimate the propagation effects, which are used to compensate for the radar echoes distorted by rainfall. Consequently, a hierarchical search strategy is employed to optimize the receiving polarization state to better discriminate the targets from rainfall and sea clutter. Simulation results show that, across the tested sea-surface wind and rainfall conditions, the proposed method improves the signal-to-clutter-plus-noise ratio (SCNR) by 4 to 13 dB compared with the polarimetric whitening filter, demonstrating its effectiveness under coupled rain–sea conditions.