Gridless sparsity-based DOA estimation for sparse linear array

被引:3
|
作者
Zhang, Yu [1 ]
Zhang, Gong [1 ]
Kong, Yingying [1 ]
Wen, Fangqing [2 ]
机构
[1] Nanjing Univ Aeronaut & Astronaut, Key Lab Radar Imaging & Microwave Photon, Minist Educ, Nanjing, Jiangsu, Peoples R China
[2] Yangtze Univ, Elect & Informat Sch, Jingzhou, Peoples R China
来源
JOURNAL OF ENGINEERING-JOE | 2019年 / 2019卷 / 20期
基金
中国国家自然科学基金;
关键词
MAXIMUM-LIKELIHOOD; SIGNAL;
D O I
10.1049/joe.2019.0143
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
A novel two-stage gridless sparsity-based method for sparse linear array direction-of-arrival (DOA) estimation is presented. First, the covariance matrix gridless sparse representation method based on atomic norm minimisation is proposed for corresponding structured Toeplitz matrix construction and source number detection. Then, the conventional MUSIC algorithm can be employed for DOA estimation. Compared with conventional subspace-based algorithms, the proposed two-stage method can be carried out without knowing source number and directly detect more source signals than sensors. Numerical simulations demonstrate the effectiveness and outperformance of the proposed method.
引用
收藏
页码:6629 / 6632
页数:4
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