Single snapshot DOA estimation by minimizing the fraction function in sparse recovery
type: Item
instance of: scholarly article
title: Single snapshot DOA estimation by minimizing the fraction function in sparse recovery
zbMATH Open document ID: 1459.94048
DOI: 10.1155/2020/6163529
author: Yanyan Li
published in: Mathematical Problems in Engineering
publication date: 2020-10-12T00:00:00Z
review text: Summary: Sparse recovery is one of the most important methods for single snapshot DOA estimation. Due to fact that the original \(l_0\)-minimization problem is a NP-hard problem, we design a new alternative fraction function to solve DOA estimation problem. First, we discuss the theoretical guarantee about the new alternative model for solving DOA estimation problem. The equivalence between the alternative model and the original model is proved. Second, we present the optimal property about this new model and a fixed point algorithm with convergence conclusion are given. Finally, some simulation experiments are provided to demonstrate the effectiveness of the new algorithm compared with the classic sparse recovery method.
Mathematics Subject Classification ID: 94A12
Mathematics Subject Classification ID: 90C26
Mathematics Subject Classification ID: 90C90
Mathematics Subject Classification ID: 65F22
zbMATH DE Number: 7259631
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1155/2020/6163529
OpenAlex ID: W3080457702
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description: scientific article; zbMATH DE number 7259631