基于改进平滑l_0范数的DOA估计算法  

DOA Estimation Algorithm Based on Improved Smoothed l_0 Norm

作　　者：单泽涛 刘小松[2] 单泽彪[2,3] 陈淼[3] 石要武[3] 

机构地区：[1]保定威奕汽车有限公司制造部,河北保定072550 [2]长春理工大学电子信息工程学院,长春130022 [3]吉林大学通信工程学院,长春130022

出　　处：《吉林大学学报（信息科学版）》2017年第6期603-607,共5页Journal of Jilin University（Information Science Edition）

基　　金：国家自然科学基金资助项目(61571462);国防基础科研计划基金资助项目(JCKY2016411C006)

摘　　要：为提高现有基于压缩感知的DOA(Direction of Arrival)估计算法估计精度,提出一种基于改进平滑l_0范数的DOA估计算法。该算法在构造一个恰当的平滑连续函数后根据接收数据的初始解确定一个合适的递减{σ}序列[σ_1,σ_2,…,σ_J],并对每个σ值,采用最速下降法求解l_0范数逼近函数F_σ(S)的最小值;然后将该σ值作为下一次迭代的初始值,并通过多次的迭代获得逼近函数的最小解,即逼近的最小l_0范数。同时通过仿真实验对该算法进行了验证。结果表明,该算法在单快拍条件下即可对DOA进行有效估计,与OMP(Orthogonal Matching Pursuit)算法相比,运算过程简单、精度较高,具有更好的估计性能。In order to improve the estimation accuracy of the existing DOA （ Direction of Arrival） estimation algorithms based on compressive sensing, a DOA estimation algorithm based on Improved Smoothed l0 norm is proposed. Firstly, we construct a proper smooth continuous function and give a proper decreasing sequence of sets {σ} which is [σ1,σ2,…,σJ based on the initial solution of receiving data to get the minimum value of Fσ （S） for every single σ by using steepest descent method, secondly we take this σ as the original value for the next iteration, and then we get the minimal solution of the smooth continuous function which is the imminent minimum l0 norm by a number of iterations. At last, we verify this p The results denote that the proposed algorithm can achieve （Orthogonal Matching Pursuit）algorithm under the condition high precision. algorithm by simulation experiments. more excellent estimation performance than OMP of single-snapshot and can get simple process and

关 键 词：阵列信号处理 DOA估计 改进平滑l0范数 最速下降法 

分 类 号：TN911[电子电信—通信与信息系统]