Radar Imaging Based on Compressed Sensing by Random Convolution

摘要：

Compressed Sensing (CS) theory provides great possibilities for resolving problems associated with traditional high resolution radar, such as high sampling rate, too many data and difficulties of real time processing. Sensing by random convolution is a universally efficient data acquisition strategy and easy to realize. This paper focuses on radar imaging technique based on CS by random convolution, researches into several different random downsampling strategies. Experiments from simulated data and real data verify the validity of the proposed imaging method, also the influences of SNR and downsampling strategy on imaging performance are analyzed and compared. Finally the problems need further research are pointed out.

关键词： Radar imaging Compressed Sensing Random convolution Downsampling

作者: Liu Jihong Xu Shaokun Gao Xunzhang Li Xiang

作者单位: Institute of Space Electronic Technology, National University of Defense Technology, Changsha, China

会议类型: 国际会议

会议名称: 2010 IEEE 10th International Conference on Signal Processing(第十届信号处理国际会议 ICSP 2010)

会议地点: 北京

会议语种:英文

页码: 2007-2010

在线出版日期: 2010-08-24（万方平台首次上网日期，不代表论文的发表时间）