High-Precision Imaging and Dense Vehicle Target Detection Method for Airborne Single-Pass Circular Synthetic Aperture Radar

Circular synthetic aperture radar (CSAR) has advantages of the omnidirectional detection and high-resolution imaging. However, when CSAR detects the dense target in the observation scene, the phenomena such as the layover effect in the CSAR image may make mutual interference between the adjacent vehicles, which leads to the poor performance of dense target detection by traditional methods. To address this problem, this article has proposed a high-precision imaging and dense vehicle target detection method for the airborne single-pass CSAR, which includes the CSAR high-precision imaging based on the extracted digital elevation model (DEM) information and high-precision dense vehicle target detection based on the CSAR image. For the high-precision imaging, the backprojection algorithm (BPA) is first used for the observation scene imaging, and then the DEM information of the vehicle target is extracted using the improved subaperture correlation method. Finally, the extracted DEM information is combined with the BPA for the high-precision imaging. For the high-precision detection, the obtained high-precision CSAR image is used to generate the maximally stable extremal region, then the extreme region is fused using the vehicle target length and width information, and finally the high-precision detection result of the dense vehicle target is obtained. Based on the public CSAR dataset from the American Air Force Research Laboratory, the experimental results show that the proposed method can obtain the high-precision CSAR images and improve the detection rate of dense vehicle target under the premise of ensuring a low false alarm rate.