Adaptive Fast Refocusing for Ship Targets with Complex Motion in SAR Images

Synthetic aperture radar (SAR) enables all-weather, round-the-clock monitoring of the oceans. Ships are subjected to complex movements by sea winds and waves while traveling, which can cause them to appear heavily defocusing in SAR images. This paper introduces an adaptive fast refocusing algorithm (AFRA) designed to refocus defocused ships. This algorithm can adaptively adjust algorithm parameters based on SAR images from different SAR platforms, thereby more accurately determining the optimal rotation interval (ORI), reducing computational cost, and achieving adaptive fast refocusing. First, each azimuth line is represented as a signal with multi-component linear frequency modulation (MC-LFM) signal. Second, by using the parameters of the SAR platform, the relationship between azimuth velocity and the optimal rotation order (ORO) is calculated, thereby determining the ORI. Third, the ORO within the ORI is computed using the Fractional Autocorrelation (FrAc). Then, each azimuth line is refocused using Fractional Fourier Transform (FrFT). Finally, the refocused image is obtained by substituting the raw azimuth lines for the refocused ones. Results from the experiments reveal that the method put forward can successfully counteract the defocusing produced by complex motion. Compared to state-of-art leading refocusing algorithm, AFRA takes only approximately 15% the time required to process Hisea-1 data with long synthetic aperture time, 27% of the time required to process Gaofen-3 data with short synthetic aperture time, and still has excellent refocusing effect.