基于压缩感知的多发多收高分辨SAR成像算法研究  

Study on Multi-transmit and Multi-receive High Resolution SAR Imaging Algorithm Based on Compressive Sensing

作　　者：常俊飞[1] 张顺生[1] 

机构地区：[1]电子科技大学,成都611731

出　　处：《火控雷达技术》2011年第4期25-31,共7页Fire Control Radar Technology

基　　金：中央高校基本科研业务费专项基金资助项目(ZYGX2010J118)

摘　　要：压缩感知理论指出,稀疏信号可以通过以低于奈奎斯特采样的测量数据重建出原始信号。针对高分辨率SAR成像在奈奎斯特理论下所面临的高速A/D采样、大数据量存储、传输等问题挑战。本文提出了一种基于压缩感知理论的多发多收高分辨率SAR二维成像算法。该算法减轻了高分辨率SAR成像的压力,采用压缩感知处理降低了A/D采样速率、数据量存储等问题,采用多发多收提高了方位向分辨率和进一步展宽了测绘带,降低了脉冲重复频率,对于高分辨率SAR成像的研究具有重要意义。通过对点目标和分布目标的仿真处理验证了算法的有效性,并且给出了压缩感知降采样倍数与重构效果之间的关系。Compressive sensing （CS） theory indicates that original signal can be reconstructed from sparse by using measured data lower than Nyquist sampling. Considering the challenges that high resolution syntheti signals caperture radar （SAR） imaging might encounter problems such as high speed A/D sampling, the large amount of data storage and transmission in Nyquist theory, a new multi-transmit and multi-receive high resolution SAR 2D imaging algorithm based on compressive sensing （CS） theory is presented. Application of this algorithm reduces pressure of high resolution SAR imaging processing, and applying compression sensing processing decreases A/D sampling rate and data storage; adopting multi-transmit and multi-receive mode can increase resolution in azimuth and extend mapping strips further, decrease the pulse repetition frequency and is very important for studying high resolution SAR imaging. The simulation results by using point targets and distributed target verify effectiveness of the algorithm, and the relationship between down-sampling multiple of compressive sensing and reconstruction effect is given.

关 键 词：压缩感知 合成孔径雷达 高分辨SAR 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]