A New Method for Joint Sparse DOA Estimation

被引:0
|
作者
Hou, Jinyong [1 ]
Wang, Changlong [1 ]
Zhao, Zixuan [1 ]
Zhou, Feng [1 ]
Zhou, Huaji [2 ]
机构
[1] Xidian Univ, Key Lab Elect Informat Countermeasure & Simulat Te, Minist Educ, Xian 710071, Peoples R China
[2] Natl Key Lab Electromagnet Space Secur, Jiaxing 314000, Peoples R China
关键词
DOA estimation; l2; th norm minimization; joint sparse reconstruction;
D O I
10.3390/s24227216
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
To tackle the issue of poor accuracy in single-snapshot data processing for Direction of Arrival (DOA) estimation in passive radar systems, this paper introduces a method for judiciously leveraging multi-snapshot data. This approach effectively enhances the accuracy of DOA estimation and spatial angle resolution in passive radar systems. Additionally, in response to the non-convex nature of the mixed norm, we propose a hyperbolic tangent model as a replacement, transforming the problem into a directly solvable convex optimization problem. The rationality of this substitution is thoroughly demonstrated. Lastly, through a comparative analysis with existing discrete grid DOA estimation methods, we illustrate the superiority of the proposed approach, particularly under conditions of medium signal-to-noise ratio, varying numbers of snapshots, and close target angles. This method is less affected by the number of array elements, and is more usable in practices verified in real-world scenarios.
引用
收藏
页数:19
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