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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Bibliographic Details

Published in:	Digital signal processing Vol. 153; p. 104628
Main Authors:	Bai, Longxin, Zhang, Jingchao, Qiao, Liyan
Format:	Journal Article
Language:	English
Published:	Elsevier Inc 01.10.2024
Subjects:	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 Access:	Get full text
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