数据采集与处理2012，Vol.27Issue(2)：138-143,6.
压缩感知雷达感知矩阵优化
Optimized Sensing Matrix Design for Compressive Sensing Radar
摘要
Abstract
The sparse scene recovery performance of compressed sensing radar (CSR) requires that the coherence parameter of the sensing matrix should be as small as possible. Based on the premise, a new optimal sensing matrix design method is proposed. To minimize the coherence parameter of the sensing matrix, the waveform and measurement matrix are designed separate ly and simultaneously using the simulated annealing (SA). Simulation results demonstrate that the algorithm can improve recovery accuracy, enhance noise immunity and increase the maxi mum permissible sparsity of CSR. Hence, the joint optimization algorithm has a better result than the algorithms which optimize waveform or measurement matrix separately.关键词
压缩感知雷达/模拟退火算法/随机多相码/感知矩阵/随机滤波器Key words
compressive sensing radar (CSR)/ simulated annealing (SA) algorithm/ random polyphase code/ sensing matrix/ random filter分类
信息技术与安全科学引用本文复制引用
潘汇,张劲东,张弓..压缩感知雷达感知矩阵优化[J].数据采集与处理,2012,27(2):138-143,6.基金项目
国家自然科学基金(61071163)资助项目 （61071163）
中国博士后基金(20100481143)资助项目 （20100481143）
南京航空航天大学校创新基金(NP2011032,NS2012020)资助项目. （NP2011032,NS2012020）
