A Fast Group Sparsity Based Phase Retrieval Algorithm for Non-Coherent DOA Estimation

Zhengyu Wan, Wei Liu

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

3 Citations (Scopus)

Abstract

A non-coherent DOA estimation algorithm for multiple snapshots is presented. The non-coherent DOA estimation problem is firstly formulated as a non-convex joint group sparsity based phase retrieval problem, and then replaced by its convex surrogate alternative through applying the majorization-minimization technique, and finally the proximal gradient method is employed to solve the surrogate problem. The proposed algorithm is referred to as fasT grOup sparsitY Based phAse Retrieval (ToyBar). Compared to the state of the art, the proposed one achieves a better performance with a lower computational complexity, as demonstrated by computer simulations.

Original languageEnglish
Title of host publicationConference Record of the 54th Asilomar Conference on Signals, Systems and Computers, ACSSC 2020
EditorsMichael B. Matthews
PublisherIEEE Computer Society
Pages220-224
Number of pages5
ISBN (Electronic)9780738131269
DOIs
Publication statusPublished - Jun 2021
Event54th Asilomar Conference on Signals, Systems and Computers, ACSSC 2020 - Pacific Grove, United States
Duration: 1 Nov 20205 Nov 2020

Publication series

NameConference Record - Asilomar Conference on Signals, Systems and Computers
Volume2020-November
ISSN (Print)1058-6393

Conference

Conference54th Asilomar Conference on Signals, Systems and Computers, ACSSC 2020
Country/TerritoryUnited States
CityPacific Grove
Period1/11/205/11/20

Keywords

  • DOA estimation
  • non-coherent
  • phase retrieval
  • proximal gradient

ASJC Scopus subject areas

  • Signal Processing
  • Computer Networks and Communications

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