西安电子科技大学学报（自然科学版）2016，Vol.43Issue(2)：58-63,101,7.DOI:10.3969/j.issn.1001-2400.2016.02.011
采用协方差矩阵稀疏表示的DOA估计方法
DOA estimation method based on the covariance matrix sparse representation
摘要
Abstract
The performance of the L1-norm-based sparse representation of array covariance vectors(L1-SRACV) algorithm significantly degrades with the number of samples decreasing. This paper analyzes the essential cause of this performance degradation and proposes a new direction of arrival(DOA) estimation method based on the fast maximum likelihood(FML) algorithm. Firstly, the FML algorithm is employed to estimate the covariance matrix, which attenuates the instability of the small eigenvalues of the covariance matrix. Then the sparse representation model based on the FML is formulated for DOA estimation and finally, optimized by removing the diagonal elements of the covariance matrix to obtain better performance. Simulation results indicate that our method outperforms the L1-SRACV with a higher accuracy and detection possibility, particularly under small samples support.关键词
稀疏表示/波达方向估计/高分辨/协方差矩阵/相关信号/快速极大似然算法Key words
sparse representation/DOA estimation/high-resolution/covariance matrix/correlative signal/fast maximum likelihood algorithm分类
信息技术与安全科学引用本文复制引用
赵永红,张林让,刘楠,解虎..采用协方差矩阵稀疏表示的DOA估计方法[J].西安电子科技大学学报（自然科学版）,2016,43(2):58-63,101,7.基金项目
中央高校基本科研业务费专项资金资助项目(JB140213) （JB140213）
