Noise Covariance Matrix Estimation in Block-Correlated Noise Field for Direction Finding

Majdoddin Esfandiari; Sergiy A. Vorobyov

doi:10.1109/LSP.2025.3525898

Noise Covariance Matrix Estimation in Block-Correlated Noise Field for Direction Finding

Majdoddin Esfandiari
, Sergiy A. Vorobyov^*

^*Tämän työn vastaava kirjoittaja

Tutkimustuotos: Lehtiartikkeli › Article › Scientific › vertaisarvioitu

1 Sitaatiot (Scopus)

140 Lataukset (Pure)

Abstrakti

A noise covariance matrix estimation approach in unknown noise field for direction finding applicable for the practically important cases of nonuniform and block-diagonal sensor noise is proposed. It is based on an alternating procedure that can be adjusted for a specific noise type. Numerical simulations are conducted in order to establish the generality and superiority of the proposed approach over the existing state-of-the-art methods, especially in challenging scenarios.

Alkuperäiskieli	Englanti
Sivut	531-535
Sivumäärä	5
Julkaisu	IEEE Signal Processing Letters
Vuosikerta	32
DOI - pysyväislinkit	https://doi.org/10.1109/LSP.2025.3525898
Tila	Julkaistu - 2025
OKM-julkaisutyyppi	A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä

Rahoitus

Received 7 November 2024; accepted 26 December 2024. Date of publication 6 January 2025; date of current version 13 January 2025. This work was supported in part by the Academy of Finland under Grant 357715. The associate editor coordinating the review of this article and approving it for publication was Dr. Wenqiang Pu. (Corresponding author: Sergiy A. Vorobyov.) The authors are with the Department of Information and Communications Engineering, Aalto University, 02150 Espoo, Finland (e-mail: [email protected]; [email protected]). Digital Object Identifier 10.1109/LSP.2025.3525898

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10.1109/LSP.2025.3525898Lisenssi: CC BY

Noise_Covariance_Matrix_Estimation_in_Block-Correlated_Noise_Field_for_Direction_FindingFinal published version, 527 KBLisenssi: CC BY

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1 Päättynyt

AI Based RAN: Towards Scalable and AI-Based Solutions for Beyond-5G Radio Access Networks
Vorobyov, S. (Vastuullinen johtaja), Palshin, A. (Projektin jäsen), Zhang, T. (Projektin jäsen), Esfandiari, M. (Projektin jäsen), Wang, X. (Projektin jäsen), Yellapragada, S. (Projektin jäsen) & Hassas Irani, K. (Projektin jäsen)
01/01/2023 → 31/12/2025
Projekti: RCF Academy Project

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title = "Noise Covariance Matrix Estimation in Block-Correlated Noise Field for Direction Finding",

abstract = "A noise covariance matrix estimation approach in unknown noise field for direction finding applicable for the practically important cases of nonuniform and block-diagonal sensor noise is proposed. It is based on an alternating procedure that can be adjusted for a specific noise type. Numerical simulations are conducted in order to establish the generality and superiority of the proposed approach over the existing state-of-the-art methods, especially in challenging scenarios.",

keywords = "Block-diagonal noise, DOA estimation, Noise covariance matrix estimation, Nonuniform noise, Unknown noise field",

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

note = "Publisher Copyright: {\textcopyright} 1994-2012 IEEE.",

year = "2025",

doi = "10.1109/LSP.2025.3525898",

language = "English",

volume = "32",

pages = "531--535",

journal = "IEEE Signal Processing Letters",

issn = "1070-9908",

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T1 - Noise Covariance Matrix Estimation in Block-Correlated Noise Field for Direction Finding

AU - Esfandiari, Majdoddin

AU - Vorobyov, Sergiy A.

PY - 2025

Y1 - 2025

N2 - A noise covariance matrix estimation approach in unknown noise field for direction finding applicable for the practically important cases of nonuniform and block-diagonal sensor noise is proposed. It is based on an alternating procedure that can be adjusted for a specific noise type. Numerical simulations are conducted in order to establish the generality and superiority of the proposed approach over the existing state-of-the-art methods, especially in challenging scenarios.

AB - A noise covariance matrix estimation approach in unknown noise field for direction finding applicable for the practically important cases of nonuniform and block-diagonal sensor noise is proposed. It is based on an alternating procedure that can be adjusted for a specific noise type. Numerical simulations are conducted in order to establish the generality and superiority of the proposed approach over the existing state-of-the-art methods, especially in challenging scenarios.

KW - Block-diagonal noise

KW - DOA estimation

KW - Noise covariance matrix estimation

KW - Nonuniform noise

KW - Unknown noise field

UR - https://www.scopus.com/pages/publications/85214705676

U2 - 10.1109/LSP.2025.3525898

DO - 10.1109/LSP.2025.3525898

M3 - Article

AN - SCOPUS:85214705676

SN - 1070-9908

VL - 32

SP - 531

EP - 535

JO - IEEE Signal Processing Letters

JF - IEEE Signal Processing Letters

ER -

Noise Covariance Matrix Estimation in Block-Correlated Noise Field for Direction Finding

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AI Based RAN: Towards Scalable and AI-Based Solutions for Beyond-5G Radio Access Networks

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