JCMF: A Novel Wideband DOA Estimator

Xiaoyu Zhang, Haihong Tao, Junqi Xue, Jian Xie, Jianpu Li, Huihui Ma

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

Covariance matrix fitting is a classic problem in direction-of-arrival (DOA) estimation, but there has been little discussion about wideband signals. In this paper, a novel wideband DOA estimation method based on covariance matrix fitting is developed. First of all, a novel wideband signal model is proposed and the wideband joint covariance matrix is formulated. The fitting criterion is deduced by the statistical characteristics of this model. Then the optimization problem of the criterion is transformed into a block sparsity problem using Holder's inequality. The problem can be divided into two subproblems and the closed-form solution of each part is obtained by dual method. The result of our wideband estimator can be solved by alternating iteration. Finally, the Cramer-Rao bound (CRB) is derived for wideband signals. Compared with other algorithms, the presented estimator has higher accuracy. Simulation results show the effectiveness and feasibility of the proposed algorithm.

Original languageEnglish
Title of host publication2021 CIE International Conference on Radar, Radar 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1589-1592
Number of pages4
ISBN (Electronic)9781665498142
DOIs
StatePublished - 2021
Event2021 CIE International Conference on Radar, Radar 2021 - Haikou, Hainan, China
Duration: 15 Dec 202119 Dec 2021

Publication series

NameProceedings of the IEEE Radar Conference
Volume2021-December
ISSN (Print)1097-5764
ISSN (Electronic)2375-5318

Conference

Conference2021 CIE International Conference on Radar, Radar 2021
Country/TerritoryChina
CityHaikou, Hainan
Period15/12/2119/12/21

Keywords

  • covariance matrix fitting
  • direction-of-arrival (DOA) estimation
  • group sparsity
  • wideband signal

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