A nonconvex sparse recovery method for DOA estimation based on the trimmed lasso

Sparse direction-of-arrival (DOA) estimation methods can be formulated as a group-sparse optimization problem. Meanwhile, sparse recovery methods based on nonconvex penalty terms have been a hot topic in recent years due to their several appealing properties. Herein, this paper studies a new nonconv...

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Veröffentlicht in:	Digital signal processing Jg. 153; S. 104628
Hauptverfasser:	Bai, Longxin, Zhang, Jingchao, Qiao, Liyan
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier Inc 01.10.2024
Schlagworte:	Direction-of-arrival estimation Majorization-minimization algorithm Nonconvex penalty Recovery guarantee The trimmed LASSO Direction-of-arrival estimation Nonconvex penalty The trimmed LASSO Recovery guarantee Majorization-minimization algorithm
ISSN:	1051-2004, 1095-4333
Online-Zugang:	Volltext
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