Synthetic aperture radar (SAR) is a suitable tool to obtain reliable wind retrievals with high spatial resolution.The geo-physical model function (GMF),which is widely employed for wind speed retrieval from SAR data,describes the relationship be-tween the SAR normalized radar cross-section (NRCS) at the copolarization channel (vertical-vertical and horizontal-horizontal) and a wind vector.SAR-measured NRCS at cross-polarization channels (horizontal-vertical and vertical-horizontal) correlates with wind speed.In this study,a semi-empirical algorithm is presented to retrieve wind speed from the noisy Chinese Gaofen-3 (GF-3) SAR data with noise-equivalent sigma zero correction using an empirical function.GF-3 SAR can acquire data in a quad-polarization strip mode,which includes cross-polarization channels.The semi-empirical algorithm is tuned using acquisitions collocated with winds from the European Center for Medium-Range Weather Forecasts.In particular,the proposed algorithm includes the dependences of wind speed and incidence angle on cross-polarized NRCS.The accuracy of SAR-derived wind speed is around 2.10 m s?1 root mean square error,which is validated against measurements from the Advanced Scatterometer onboard the Metop-A/B and the buoys from the National Data Buoy Center of the National Oceanic and Atmospheric Administration.The results obtained by the proposed algo-rithm considering the incidence angle in a GMF are relatively more accurate than those achieved by other algorithms.This work provides an altative method to generate operational wind products for GF-3 SAR without relying on ancillary data for wind direc-tion.