An Adaptive GaoFen-3 SAR Wind Field Retrieval Algorithm Based on Information Entropy

Abstract

Chinese GaoFen-3 (GF-3) synthetic aperture radar (SAR) imagery acquired in standard strip mode can capture streak features caused by wind over the sea surface, which are commonly known as wind streaks. To retrieve the sea surface wind field from a GF-3 SAR image, an adaptive wind retrieval algorithm based on information entropy is proposed in this paper. This algorithm can adaptively extract the optimal wavenumber range of each subimage based on maximum information entropy. After all subimages are processed for possible wind streak direction solutions, a circle median filter is used to determine the unique wind streak direction solution for each subimage. Twelve GF-3 standard strip SAR images are inverted to validate the proposed algorithm. The experiments show that when the GF-3 image data are compared to the European Centre for Medium-Range Weather Forecasts reanalysis wind field data, the root mean square error of wind speed and direction retrieved by the algorithm are 1.29 m/s and 15.33°, respectively, and when they are compared to the National Data Buoy Center buoy wind data, the mean absolute deviation errors of wind speed and direction are 0.57 m/s and 9.95°, respectively. These comparisons demonstrate that the proposed algorithm can effectively retrieve wind field information from GF-3 SAR images.

Keywords

• GaoFen-3 satellite
• synthetic aperture radar
• wind retrieval
• wind streak
• information entropy