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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Vydané v:	Digital signal processing Ročník 153; s. 104628
Hlavní autori:	Bai, Longxin, Zhang, Jingchao, Qiao, Liyan
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier Inc 01.10.2024
Predmet:	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
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