基于l_1稀疏正则化的信源个数估计新算法  

New source number estimation algorithm based on l_1 sparse regularization

作　　者：金芳晓 邱天爽[1] 王鹏[1] 夏楠[2] 李景春[2] 

机构地区：[1]大连理工大学电子信息与电气工程学部,辽宁大连116024 [2]国家无线电监测中心,北京100037

出　　处：《通信学报》2016年第10期75-80,共6页Journal on Communications

基　　金：国家自然科学基金资助项目(No.61139001;No.61172108;No.81241059;No.61501301);国家科技支撑计划基金资助项目(No.2012BAJ18B06-04)~~

摘　　要：针对现有信号源个数估计相关算法在低信噪比和较少快拍数下存在欠估计的问题,提出一种适用于空间平稳噪声下基于l1稀疏正则化的信源个数估计新算法。该算法利用信号协方差矩阵特征值分解得到的特征值序列的稀疏性,选取合适的正则化参数对信号源个数进行估计。理论分析和仿真实验表明,所提算法可以在较低信噪比的空间平稳噪声条件下,实现对较少快拍数下阵列接收数据信源个数的精确估计。In view of the problems of inefficient in low SNR and less snapshots when using existing sources number es- timation related algorithms, a new algorithm based on 1i sparse regularization under space stationary noise was proposed to estimate the number of signal sources. The algorithm estimated the sources number by using the sparse representation of eigenvalues vectors with the suitable regularization parameter. Theoretical analysis and simulation results show that the algorithm can realize an accurate sources number estimation in low SNR and less snapshots.

关 键 词：稀疏正则化 信源个数估计 空间平稳噪声 正则化参数 

分 类 号：TN911.7[电子电信—通信与信息系统]