l_1-analysis稀疏重构在阵列信号恢复及波达角估计中的应用  

Reconstruction of array output and direction-of-arrival estimation via l_1-analysis sparse recovery

作　　者：林波[1] 张增辉[1] 朱炬波[1] 

机构地区：[1]国防科技大学理学院,湖南长沙410073

出　　处：《国防科技大学学报》2013年第5期152-157,共6页Journal of National University of Defense Technology

基　　金：国家自然科学基金资助项目(60901071;61002024;61102169;61201332);国防科学技术大学科研计划项目(JC11-02-03)

摘　　要：通过适当的空域稀疏化构造了可对阵列接收信号进行冗余稀疏表示的阵列流形矩阵,建立了相应的l1-analysis稀疏重构模型,用于恢复阵列接收信号,重点证明了该流形矩阵是满足l1-analysis稀疏重构条件的紧框架,从理论上保证了将l1-analysis稀疏重构用于阵列接收信号恢复及波达角估计问题的合理性,并推导出信号恢复误差的理论上界。利用在微波暗室环境中采集的实测数据,结合MUSIC算法进行实验验证,结果表明基于l1-analysis稀疏重构的信号恢复对提高低信噪比环境下的波达角估计性能是有效的。The array manifold matrix was constructed as a redundant dictionary in which the array receiving signals were sparse through the appropriate spatial sparse division,and the corresponding （l1）-analysis sparse recovery model was established to reconstruct the array output data.The core of this paper is to prove that the manifold matrix is a tight frame and can satisfy the condition which guarantees the accurate recovery of signals through （l1）-analysis sparse recovery so that it is reasonable enough to use （l1）-analysis sparseness optimization to reconstruct the array output data.The upper bound of reconstruction error was given.The effectiveness of this presented method for improving the performance of DOA estimation with low SNR was verified by the experiments using the actual measurement data received in microwave darkroom through MUSIC algorithm.

关 键 词：(l1)-analysis稀疏重构 冗余稀疏表示 阵列信号处理 波达角估计 低信噪比 

分 类 号：TN911[电子电信—通信与信息系统]