基于消卷积的三维成像雷达散射截面测量技术

Three-dimensional Imaging Radar Cross Section Measurement Technology Based on Deconvolution

基于三维成像雷达散射截面积(radar cross section,RCS)测量技术是近年新兴的一种灵活、高效的RCS测量技术。该技术基于三维线阵合成孔径雷达(synthetic aperture radar,SAR)测量系统对目标进行近场三维高分辨成像,通过近远场变换算法,得到目标的远场RCS,具备近场、外场测量能力。基于成像的RCS测量,其成像精度直接影响RCS的测量精度。为了得到高质量的RCS结果,就需要得到高分辨的图像。采用压缩感知三维成像算法对目标进行成像,有效提高了RCS的反演精度,并分析了改进CLEAN算法的抑制旁瓣原理,得出两种方法都是基于消卷积原理对旁瓣进行抑制。用MATLAB和FEKO测量仿真,结果表明压缩感知算法提取散射中心效果更好,且提高了RCS的反演精度。

Radar cross section(RCS)measurement technology based on three-dimensional imaging is a flexible and efficient RCS measurement technology that has emerged in recent years.The technology is based on a three-dimensional linear array synthetic aperture radar(SAR)measurement system to perform near-field three-dimensional high-resolution imaging of the target,and obtain the far-field RCS of the target through the near-far-field transformation algorithm.Both near-field and outer-field measurements can be achieved by this technology.The measurement accuracy of RCS is directly affected by the imaging accuracy of the target.In order to obtain high-quality RCS results,it is necessary to obtain high-resolution images.The compressed sensing three-dimensional imaging algorithm was used to image the target,which effectively improved the inversion accuracy of RCS,and the principle of sidelobe suppression of the improved CLEAN algorithm was analyzed.It is concluded that the two methods are based on the principle of deconvolution to suppress sidelobes.The simulation results of MATLAB and FEKO show that the compressed sensing algorithm can more effectively extract the scattering center and improve the inversion accuracy of RCS.