计算机应用研究2013，Vol.30Issue(2)：537-540,4.DOI:10.3969/j.issn.1001-3695.2013.02.060
基于稀疏表示的信号DOA估计
Sparse representation perspective for source localization based on JSL0-SVD
摘要
Abstract
The source localization problem was cast as the problem of recovering a joint sparse representation. It used the singular value decomposition of the data matrix to summarize multiple time and frequency samples,then imposed the smoothed l0 norm to enforce sparsity and used a fixed-point iteration approach to solve the joint optimization problem. The proposed algorithm has the following advantages: improved robustness to noise, improved computation efficiency, robustness to limited number of samples, robustness to correlated sources, no requirement of accurate initialization. The performance of the proposed method was compared to standard spectrum based approaches and other sparse based methods.关键词
到达角/奇异值分解/联合稀疏/平滑l0范数Key words
DOA/singular value decomposition/joint sparse/smoothed l0 norm分类
信息技术与安全科学引用本文复制引用
冯莹莹,程向阳,邓明..基于稀疏表示的信号DOA估计[J].计算机应用研究,2013,30(2):537-540,4.基金项目
安徽高校省级科学研究项目(KJ2012B138) （KJ2012B138）
安徽省质量工程项目(20101985) （20101985）
