变步长SAMP算法在雷达目标识别中的应用  

Application of a Variable Step Size SAMP Algorithm in Radar Target Recognition

作　　者：赵东波 李辉[2] ZHANG Dong-bo;LI Hui(School of electronic engineering,Xi＇an Aeronautical University,Xi＇an 710077,China;School of electronic engineering,Northwestern Polytechnical University,Xi＇an 710129,China)

机构地区：[1]西安航空学院电子工程学院,西安710077 [2]西北工业大学电子信息学院,西安710129

出　　处：《控制工程》2018年第8期1381-1385,共5页Control Engineering of China

基　　金：国家自然科学基金项目(61571364);陕西省自然科学基金项目(2017JM6037)

摘　　要：引入压缩感知（CS）理论采用压缩重构的方法来解决雷达回波信号的数据巨大的问题。在信号稀疏度未知的情况下,针对传统的SAMP算法步长S固定导致的过估计或迭代时间过长问题,提出一种变步长的稀疏度自适应匹配追踪算法（Vs SAMP）。该算法在运算过程中以大步长快速逼近小步长慢速接近的原则,通过设置阈值调整步长变化来提高重构率。通过对雷达高分辨率距离像实测数据的压缩重构实验表明,与现有贪婪算法相比,变步长的自适应匹配追踪算法（Vs SAMP）可以用较快的速度和更高的精度实现重构。The compressed sensing（CS） theory is introduced to solve the problem of huge data of radar echo signal. Under the condition of unknown signal sparsity, a variable step size sparsity adaptive matching pursuit algorithm（Vs SAMP） is proposed to solve the problem of over estimation or too long iterative time caused by the fixed S of traditional SAMP algorithm. In the process of operation, with the principle of large step fast approaching and small step slow approaching, the algorithm improves the rate of reconfiguration by setting the threshold to adjust the change of step length. The compression and reconstruction experiments of radar high resolution range profile data show that the variable step size adaptive matching pursuit algorithm（Vs SAMP） can achieve reconstruction with faster speed and higher accuracy compared with the existing greedy algorithm.

关 键 词：压缩感知 匹配追踪 自适应 SAMP算法 

分 类 号：TP391.9[自动化与计算机技术—计算机应用技术]