基于压缩感知的随机噪声成像雷达

Random Noise Imaging Radar Based on Compressed Sensing

近年来提出的压缩感知(CS)理论指出可以从很少的采样点中以很大的概率准确重建原始的未知稀疏信号。该文将压缩感知与随机噪声雷达相结合,提出了基于压缩感知的随机噪声雷达,并给出了该雷达系统的基本原理框图,从理论上证明了基于压缩感知的随机噪声雷达的回波观测矩阵具有很好的等容性质,在目标场景稀疏或可以稀疏表示时,基于压缩感知的随机噪声雷达可以采集远小于常规随机噪声雷达成像所需的回波数据并能实现准确成像,最后通过仿真实验验证了该文的结论。

Recent theory of Compressed Sensing（CS） suggests that exact recovery of an unknown sparse signal can be achieved from few measurements with overwhelming probability.In this paper,CS technology is combined with random noise radar and the concept of random noise radar is proposed based on CS.The block diagram of the radar system is presented.Detailed analysis show that the sensing matrix of the random noise radar based on CS exerts good Restricted Isometry Property（RIP）.Given a sparse or transform sparse target scene,the random nose radar based on CS can get high accuracy image by collecting far less amount of echo data than conventional noise radar does.Finally,in this paper,the conclusions are all demonstrated by simulation experiments.