In the dual-parameter CFAR detection, three windows are set, namely the target window, the protection window and the background window. The window size and the sliding step length must be obtained through empirical training, which is inefficient and may cause missed detection of SAR images of ships that are very close. In view of these shortcomings, this paper proposes an improved dual-parameter CFAR detection algorithm, which only takes the target window and the background window, removes the part of the ship that leaks into the background window, and estimates the mean and variance of the remaining part in the background window to detect the ship, and takes the window sliding step length as the target window size. Compared with the dual-parameter CFAR algorithm, the structure is simplified, the false alarm rate of the detection result is reduced, there will be no missed detection of ships that are very close, and the calculation efficiency is improved. The simulation results show the effectiveness of the method.
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