压缩感知成像雷达干扰抑制方法研究

Compressed sensing (CS) radar technology becomes an active reasearch field in radar imaging, since it has potential to resovle many problems such as high sampling rate , and large data to process. However, CS radar has the deficiency that the outside interference has a serious influence on its reconstruction precision. With the development of CS radar, it is urgent to solve the problem how CS radar can work in the real electromagnetic environment. In this research subject, multi-channel cancellation, beamforming and polarization filtering methods will be in combination with the CS theory, based on the idea of the traditional space-domain and polarization-domain interference suppression technologies. Firstly, the received signal models in space domain and polarization domain will be established and the influence on CS reconstruction precision brought about by different types of interference is analyzed. Secondly, the new work system will be designed, and the data collected at some slow times is utilized to estimated the direction of angle of the interference source, the weighted vector for beam-forming and the interference polorization parameters in higher precision. Thirdly, the CS signal models will be estabilshed after interference suppression, and the CS reconstruction algorithms are improved to reduce the impact from the residual interference. Finally, the radar image will be obtained in a high resolution. The findings may offer new guidance and theory foundation for the design of CS imaging radar system to suppress the outside interference.

压缩感知雷达可解决传统高分辨率雷达高采样率、大数据量等问题，已成为雷达成像领域的研究热点。然而，压缩感知雷达也有一个不足，那就是它的重构精度受外部干扰的影响比较大。随着压缩感知成像技术的不断深入，如何抑制现实环境中的各种电磁干扰已成为亟待解决的问题。本项目将借鉴传统雷达空域和极化域抗干扰思想，试图将多通道对消、波束形成和极化滤波等技术与压缩感知理论相结合。首先建立空域和极化域下压缩感知雷达的信号接收模型，分析各种干扰样式对压缩感知成像的影响机理；设计相应干扰方法下雷达工作机制；结合多个慢时刻接收数据，研究干扰源波达角、波束形成加权矢量和干扰信号极化参数的高精度估计方法；建立干扰抑制后的压缩感知模型，对稀疏重构算法进行改进以降低残余干扰的影响，最终实现对成像场景的高分辨重构。研究成果将为干扰条件下压缩感知成像雷达系统设计提供新的思路和理论依据。

本课题为解决压缩感知成像雷达在实用化进程中面对复杂电磁环境时出现性能下降问题而展开，深入挖掘时频域、空域和极化域上雷达有用回波与常见干扰信号之间的差异特征，将传统干扰抑制方法与压缩感知理论进行改进和融合，使压缩感知成像雷达的抗干扰理论得到了较好的补充和完善。在时频域上，课题利用了干扰功率远比回波大的特点，从时频分布上滤除干扰分量，建立了回波STFT变换与距离像之间的线性关系模型，利用压缩感知重构算法获得了无干扰的高分辨率距离像。在空域上，课题提出了多通道对消和波束自适应形成的方法来抑制干扰。在多通道对消技术中，课题提出了主被动模式交替工作的数据采集模式，利用被动接收模式对干扰辐射源的位置进行精准定位，由此获得主动模式下干扰信号到达角，并通过多通道对消的技术进行干扰抑制，建立了对消后残余信号与场景之间的线性关系模型，最后利用压缩感知理论对成像场景进行了高分辨率重构。在波束自适应形成技术中，课题利用被动模式来获得主瓣干扰信号正交空间的估计，以此构建特征投影矩阵先抑制主瓣干扰，再重构了干扰协方差矩阵并利用常规波束形成技术抑制旁瓣干扰，最后利用压缩感知实现了场景重构。在极化域上，课题利用干扰信号和回波之间的不相干性，提出了利用极化对消后距离像熵最小化来估计干扰极化比的参数估计方法，建立了极化对消后残余信号与场景之间的线性观测模型，最后根据稀疏重构算法获得高分辨率目标像。. 课题所提理论和方法经过仿真试验验证，对于主旁瓣干扰具有较好的抑制效果，可有效保证压缩感知成像雷达在复杂电磁环境下的工作性能。