Enhanced standard ESPRIT for overcoming imperfections in DOA estimation

Majdoddin Esfandiari; Sergiy A. Vorobyov

doi:10.1109/ICASSP39728.2021.9413726

Enhanced standard ESPRIT for overcoming imperfections in DOA estimation

Majdoddin Esfandiari, Sergiy A. Vorobyov

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-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 language	English
Title of host publication	ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Publisher	IEEE
Pages	4375-4379
Number of pages	5
Volume	2021-June
DOIs	https://doi.org/10.1109/ICASSP39728.2021.9413726
Publication status	Published - 2021
MoE publication type	A4 Article in a conference publication
Event	IEEE International Conference on Acoustics, Speech and Signal Processing - Toronto, Canada Duration: 6 Jun 2021 → 11 Jun 2021

Publication series

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

Conference

Conference	IEEE International Conference on Acoustics, Speech and Signal Processing
Abbreviated title	ICASSP
Country/Territory	Canada
City	Toronto
Period	06/06/2021 → 11/06/2021

Keywords

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

Access to Document

10.1109/ICASSP39728.2021.9413726

Cite this

Esfandiari, M., & Vorobyov, S. A. (2021). Enhanced standard ESPRIT for overcoming imperfections in DOA estimation. In ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings (Vol. 2021-June, pp. 4375-4379). (IEEE International Conference on Acoustics, Speech and Signal Processing). IEEE. https://doi.org/10.1109/ICASSP39728.2021.9413726

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title = "Enhanced standard ESPRIT for overcoming imperfections in DOA estimation",

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.",

keywords = "DOA estimation, ESPRIT, Generalized least squares (GLS), Small sample size",

author = "Majdoddin Esfandiari and Vorobyov, {Sergiy A.}",

note = "Funding Information: This work was supported in part by Academy of Finland under Research Grant 319822. Publisher Copyright: {\textcopyright} 2021 IEEE; IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP ; Conference date: 06-06-2021 Through 11-06-2021",

year = "2021",

doi = "10.1109/ICASSP39728.2021.9413726",

language = "English",

volume = "2021-June",

series = "IEEE International Conference on Acoustics, Speech and Signal Processing",

publisher = "IEEE",

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Esfandiari, M & Vorobyov, SA 2021, Enhanced standard ESPRIT for overcoming imperfections in DOA estimation. in ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings. vol. 2021-June, IEEE International Conference on Acoustics, Speech and Signal Processing, IEEE, pp. 4375-4379, IEEE International Conference on Acoustics, Speech and Signal Processing, Toronto, Ontario, Canada, 06/06/2021. https://doi.org/10.1109/ICASSP39728.2021.9413726

Enhanced standard ESPRIT for overcoming imperfections in DOA estimation. / Esfandiari, Majdoddin ; Vorobyov, Sergiy A.

ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings. Vol. 2021-June IEEE, 2021. p. 4375-4379 (IEEE International Conference on Acoustics, Speech and Signal Processing).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

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AU - Vorobyov, Sergiy A.

PY - 2021

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N2 - 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.

AB - 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.

KW - DOA estimation

KW - ESPRIT

KW - Generalized least squares (GLS)

KW - Small sample size

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DO - 10.1109/ICASSP39728.2021.9413726

M3 - Conference contribution

AN - SCOPUS:85115099842

VL - 2021-June

T3 - IEEE International Conference on Acoustics, Speech and Signal Processing

SP - 4375

EP - 4379

BT - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

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T2 - IEEE International Conference on Acoustics, Speech and Signal Processing

Y2 - 6 June 2021 through 11 June 2021

ER -

Enhanced standard ESPRIT for overcoming imperfections in DOA estimation

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MASSIVE AND SPARSE ANTENNA ARRAY PROCESSING FOR MILLIMETERWAVE COMMUNICATIONS

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Enhanced standard ESPRIT for overcoming imperfections in DOA estimation

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MASSIVE AND SPARSE ANTENNA ARRAY PROCESSING FOR MILLIMETERWAVE COMMUNICATIONS

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