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为了获取基于模板图像的车辆、飞机等复杂目标识别所需的海量高质量逆合成孔径雷达(ISAR)图像,提出了表面粗糙的复杂目标全极化ISAR图像快速仿真方法。该方法预先对车辆和飞机等复杂目标表面粗糙程度进行分级定量描述,并以改进的射线弹跳法和等效边缘流法快速预估来自目标粗糙表面的镜面反射和多次反射贡献以及细分边缘的绕射贡献,经相干叠加获得目标的精确电磁散射数据,最后进行成像处理得到高质量全极化ISAR图像。标准体、飞机和车辆目标的仿真实验结果验证了该方法的准确性和有效性。
In order to obtain massive high quality inverse synthetic aperture radar (ISAR) images for vehicle, aircraft and other complex target recognition based on template images, a fast target simulation method for ISAR images with complex surface and rough surface is proposed. The method pre-quantifies the surface roughness of complex targets such as vehicles and aircraft, and uses the improved ray bouncing method and equivalent edge flow method to quickly estimate the specular reflection and multiple reflection contributions from the target rough surface and subdivide the edge Of the diffraction contribution, the coherent superposition of the target to obtain accurate electromagnetic scattering data, and finally imaging processing to get high-quality fully polarized ISAR images. The simulation results of standard body, aircraft and vehicle target verify the accuracy and effectiveness of the method.