基于改进型CLEAN算法三维成像的雷达散射截面积反演

基于三维成像的雷达散射截面积(radar cross section,RCS)测量可以获得目标散射系数的三维空间分布,与一维和二维RCS测量相比,它具有更好的空间分辨能力.但是,在基于成像的RCS测量中,散射中心的提取至关重要,它在很大程度上决定着RCS的反演精度.采用CLEAN算法完成对目标散射中心的提取,有效抑制了图像的三维旁瓣,并针对CLEAN算法存在估计误差的迭代累加效应,设计了一种可以更新估计的改进的相干CLEAN算法,进一步提高了RCS的反演精度.用MATLAB和FEKO测量仿真,结果表明改进型CLEAN算法能更有效地提取散射中心,且提高了RCS的反演精度.

Radar cross section area inversion based on improved clean algorithm for 3D imaging

Radar cross section (RCS) measurement based on three-dimensional imaging can obtain the three-dimensional spatial distribution of the target scattering coefficient. Compared with one-dimensional and two-dimensional RCS measurement, it has better spatial resolution. However, in the RCS measurement based on imaging, the extraction of scattering center is very important, which determines the accuracy of RCS inversion to a large extent. In this paper, clean algorithm is used to extract the scattering center of the target, which effectively suppresses the three-dimensional side lobe of the image. Aiming at the iterative accumulation effect of estimation error in clean algorithm, an improved coherent clean algorithm which can update the estimation is designed to further improve the accuracy of RCS inversion. The simulation results of MATLAB and FEKO show that the improved clean algorithm can extract the scattering center more effectively and improve the accuracy of RCS inversion.