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^*

^*Corresponding author for this work

Research output: Contribution to journal › Article › Scientific › peer-review

1 Citation (Scopus)

143 Downloads (Pure)

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.

Original language	English
Pages (from-to)	531-535
Number of pages	5
Journal	IEEE Signal Processing Letters
Volume	32
DOIs	https://doi.org/10.1109/LSP.2025.3525898
Publication status	Published - 2025
MoE publication type	A1 Journal article-refereed

Funding

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

Keywords

Block-diagonal noise
DOA estimation
Noise covariance matrix estimation
Nonuniform noise
Unknown noise field

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Cite this

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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.\}",

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AU - Vorobyov, Sergiy A.

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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

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

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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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