Enhanced standard ESPRIT for overcoming imperfections in DOA estimation

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

Abstract

Direction-of-arrival (DOA) estimation problem is a challenging one in the presence of coherent sources, when the sample size is small, and the signal-to-noise ratio is low. We address this problem by developing a new method called enhanced standard ESPRIT (ES ESPRIT), and also its unitary extension called enhanced unitary ESPRIT (EU ESPRIT). The proposed methods use statistics of the subspace perturbation. First, they generate 2K DOA candidates for K sources, and then discreetly select K of them. Numerical results show the superiority of EU ESPRIT over other existing methods especially in improving threshold performance and separating closely located sources with a small sample size.

Original languageEnglish
Title of host publicationICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
PublisherIEEE
Pages4375-4379
Number of pages5
Volume2021-June
DOIs
Publication statusPublished - 2021
MoE publication typeA4 Article in a conference publication
EventIEEE International Conference on Acoustics, Speech and Signal Processing - Toronto, Canada
Duration: 6 Jun 202111 Jun 2021

Publication series

NameIEEE International Conference on Acoustics, Speech and Signal Processing
ISSN (Print)1520-6149
ISSN (Electronic)2379-190X

Conference

ConferenceIEEE International Conference on Acoustics, Speech and Signal Processing
Abbreviated titleICASSP
Country/TerritoryCanada
CityToronto
Period06/06/202111/06/2021

Keywords

  • DOA estimation
  • ESPRIT
  • Generalized least squares (GLS)
  • Small sample size

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