Optimized Estimation of Azimuth Cutoff for Retrieval of Significant Wave Height and Wind Speed From Polarimetric Gaofen-3 SAR Wave Mode Data

This study presents an innovative approach for estimating the azimuth cutoff wavelength (lambda(c)) using a multipolarization combination technique to enhance the retrieval of significant wave height (SWH) and wind speed (WS) from Gaofen-3 (GF-3) SAR wave mode data. The study identifies distinct advantages of copolarization for low to moderate sea states and cross-polarization for high sea states in the lambda(c) estimation. Consequently, a suite of dual and quad-polarization combination methods is proposed, with the VV+VH combination demonstrating superior cost-efficiency, reducing the root mean square error (RMSE) of lambda(c) estimation by around 20% compared with VV polarization. Correlation analysis between lambda(c) at various polarizations, particularly VV+VH, and factors such as SWH, WS, wind direction, wave direction, and incidence angle, indicates a strong positive relationship with SWH and WS, and a moderate relationship with incidence angle. This insight informs the development of three lambda(c)-based SWH and WS retrieval models: single linear regression, multiple linear regression (MLR), and Gaussian process regression (GPR). The MLR and GPR models integrate normalized radar cross section (NRCS) and incidence angle to improve retrieval accuracy. The GPR model achieves more accurate estimation of SWH and WS compared with existing lambda(c)-based algorithms, with an RMSE of 0.485 m for SWH retrieval and 1.390 m/s for WS retrieval. Despite the performance gap with state-of-the-art algorithms, the GPR model offers exceptional cost-effectiveness and surpasses NRCS-based models for WS retrieval without requiring wind direction input.