Multi-source Fusion CFAR Detection Method Based on the Contrast of Sliding Window

With the rapid development of space-ground cross domain cooperative technology, multi-source fusion detection based on multistatic radar can be achieved by means of its special configuration. However, the existing constant false alarm ratio (CFAR) detection algorithms have not yet proposed a suitable fusion detection theory for multi-station configuration. In this paper, a novel multi-source fusion CFAR detection method based on the contrast of sliding window is presented. Firstly, the feature distribution difference between the target area and the background unit is pointed out in the fused image based on the mapping relationship between the ground grid of the rectangular coordinate and the range loop of receiving station. Then, the fusion detection quantity of exponential likehood ratio is constructed, which increases the contrast between target resolution unit and background resolution unit effectively. Finally, the CFAR detection threshold based on second-order statistics of exponential likehood ratio is derived according to the system false alarm index, and thus to form a novel fusion detection theory with regard to multi-station configuration. The proposed algorithm fully exploits the target distribution characteristics in multi-source fusion image, which provides an effective way for target enhancement detection. Simulation results verify the effectiveness of the proposed algorithm.