Matrix Reconstruction to Estimate Direction of Arrival of Coherent Sources Based on Planar Array

Hao Zhang; Dong Zhen; Fang Zeng; Guojin Feng; Zhaozong Meng; Fengshou Gu

doi:10.1109/PHM2022-London52454.2022.00030

Matrix Reconstruction to Estimate Direction of Arrival of Coherent Sources Based on Planar Array

Hao Zhang, Dong Zhen, Fang Zeng, Guojin Feng, Zhaozong Meng, Fengshou Gu

Hebei University of Technology

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

Abstract

The Multiple Signal Classification (MUSIC) algorithm has become a landmark algorithm in the theoretical system of spatial spectrum estimation. This technology has excellent estimation performance and wide application prospects. Accurate Direction of Arrival (DOA) estimation plays a pivotal role in the detection of narrow wave sources. Nevertheless, when the signals are partially correlated or even coherent, the performance of the traditional MUSIC algorithm is greatly reduced. Methods such as spatial smoothing and Toeplitz matrix reconstruction have been proposed to decoherence and minimize the DOA estimation error in the MUSIC algorithm. However, these methods can only be applied to uniform linear arrays, which greatly reduces the practicability of the algorithm. This paper proposes to combine a decoherence method with MUSIC algorithm to estimate the azimuth angle (θ) and elevation angle (ϕ) of the source in a planar array which is composed of two orthogonal minimum redundant linear arrays (MRLA). The algorithm is implemented under different Signal-to-Noise Ratio (SNR) and compared with other decoherence methods. Simulation results show the proposed decoherence algorithm can achieve higher DOA estimation accuracy for coherent sources.

Original language	English
Title of host publication	Proceedings - 2022 Prognostics and Health Management Conference, PHM-London 2022
Editors	Chuan Li, Gianluca Valentino, Ling Kang, Diego Cabrera, Dejan Gjorgjevikj
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	127-131
Number of pages	5
ISBN (Electronic)	9781665479547
ISBN (Print)	9781665479554
DOIs	https://doi.org/10.1109/PHM2022-London52454.2022.00030
Publication status	Published - 1 Jul 2022
Event	2022 Prognostics and Health Management Conference - London, United Kingdom Duration: 27 May 2022 → 29 May 2022

Publication series

Name	Proceedings - 2022 Prognostics and Health Management Conference, PHM-London 2022
Publisher	IEEE
ISSN (Print)	2166-563X
ISSN (Electronic)	2166-5656

Conference

Conference	2022 Prognostics and Health Management Conference
Abbreviated title	PHM-London 2022
Country/Territory	United Kingdom
City	London
Period	27/05/22 → 29/05/22

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 9 Industry, Innovation, and Infrastructure

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10.1109/PHM2022-London52454.2022.00030Licence: Unspecified

Cite this

Zhang, H., Zhen, D., Zeng, F., Feng, G., Meng, Z., & Gu, F. (2022). Matrix Reconstruction to Estimate Direction of Arrival of Coherent Sources Based on Planar Array. In C. Li, G. Valentino, L. Kang, D. Cabrera, & D. Gjorgjevikj (Eds.), Proceedings - 2022 Prognostics and Health Management Conference, PHM-London 2022 (pp. 127-131). Article 9808803 (Proceedings - 2022 Prognostics and Health Management Conference, PHM-London 2022). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/PHM2022-London52454.2022.00030

Zhang, Hao ; Zhen, Dong ; Zeng, Fang et al. / Matrix Reconstruction to Estimate Direction of Arrival of Coherent Sources Based on Planar Array. Proceedings - 2022 Prognostics and Health Management Conference, PHM-London 2022. editor / Chuan Li ; Gianluca Valentino ; Ling Kang ; Diego Cabrera ; Dejan Gjorgjevikj. Institute of Electrical and Electronics Engineers Inc., 2022. pp. 127-131 (Proceedings - 2022 Prognostics and Health Management Conference, PHM-London 2022).

@inproceedings{ed38d88ac8104dc291a6510441554dc4,

title = "Matrix Reconstruction to Estimate Direction of Arrival of Coherent Sources Based on Planar Array",

abstract = "The Multiple Signal Classification (MUSIC) algorithm has become a landmark algorithm in the theoretical system of spatial spectrum estimation. This technology has excellent estimation performance and wide application prospects. Accurate Direction of Arrival (DOA) estimation plays a pivotal role in the detection of narrow wave sources. Nevertheless, when the signals are partially correlated or even coherent, the performance of the traditional MUSIC algorithm is greatly reduced. Methods such as spatial smoothing and Toeplitz matrix reconstruction have been proposed to decoherence and minimize the DOA estimation error in the MUSIC algorithm. However, these methods can only be applied to uniform linear arrays, which greatly reduces the practicability of the algorithm. This paper proposes to combine a decoherence method with MUSIC algorithm to estimate the azimuth angle (θ) and elevation angle (ϕ) of the source in a planar array which is composed of two orthogonal minimum redundant linear arrays (MRLA). The algorithm is implemented under different Signal-to-Noise Ratio (SNR) and compared with other decoherence methods. Simulation results show the proposed decoherence algorithm can achieve higher DOA estimation accuracy for coherent sources. ",

keywords = "Coherent sources, Direction of arrival, Matrix reconstruction, Minimum redundant linear arrays, Planar array",

author = "Hao Zhang and Dong Zhen and Fang Zeng and Guojin Feng and Zhaozong Meng and Fengshou Gu",

note = "Funding Information: ACKNOWLEDGMENT The work was supported by the National Natural Science Foundation of China under Grant No. 51875166.The support is gratefully acknowledged. Publisher Copyright: {\textcopyright} 2022 IEEE.; 2022 Prognostics and Health Management Conference, PHM-London 2022 ; Conference date: 27-05-2022 Through 29-05-2022",

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doi = "10.1109/PHM2022-London52454.2022.00030",

language = "English",

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publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "127--131",

editor = "Chuan Li and Gianluca Valentino and Ling Kang and Diego Cabrera and Dejan Gjorgjevikj",

booktitle = "Proceedings - 2022 Prognostics and Health Management Conference, PHM-London 2022",

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}

Zhang, H, Zhen, D, Zeng, F, Feng, G, Meng, Z & Gu, F 2022, Matrix Reconstruction to Estimate Direction of Arrival of Coherent Sources Based on Planar Array. in C Li, G Valentino, L Kang, D Cabrera & D Gjorgjevikj (eds), Proceedings - 2022 Prognostics and Health Management Conference, PHM-London 2022., 9808803, Proceedings - 2022 Prognostics and Health Management Conference, PHM-London 2022, Institute of Electrical and Electronics Engineers Inc., pp. 127-131, 2022 Prognostics and Health Management Conference, London, United Kingdom, 27/05/22. https://doi.org/10.1109/PHM2022-London52454.2022.00030

Matrix Reconstruction to Estimate Direction of Arrival of Coherent Sources Based on Planar Array. / Zhang, Hao; Zhen, Dong; Zeng, Fang et al.
Proceedings - 2022 Prognostics and Health Management Conference, PHM-London 2022. ed. / Chuan Li; Gianluca Valentino; Ling Kang; Diego Cabrera; Dejan Gjorgjevikj. Institute of Electrical and Electronics Engineers Inc., 2022. p. 127-131 9808803 (Proceedings - 2022 Prognostics and Health Management Conference, PHM-London 2022).

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

TY - GEN

T1 - Matrix Reconstruction to Estimate Direction of Arrival of Coherent Sources Based on Planar Array

AU - Zhang, Hao

AU - Zhen, Dong

AU - Zeng, Fang

AU - Feng, Guojin

AU - Meng, Zhaozong

AU - Gu, Fengshou

N1 - Funding Information: ACKNOWLEDGMENT The work was supported by the National Natural Science Foundation of China under Grant No. 51875166.The support is gratefully acknowledged. Publisher Copyright: © 2022 IEEE.

PY - 2022/7/1

Y1 - 2022/7/1

N2 - The Multiple Signal Classification (MUSIC) algorithm has become a landmark algorithm in the theoretical system of spatial spectrum estimation. This technology has excellent estimation performance and wide application prospects. Accurate Direction of Arrival (DOA) estimation plays a pivotal role in the detection of narrow wave sources. Nevertheless, when the signals are partially correlated or even coherent, the performance of the traditional MUSIC algorithm is greatly reduced. Methods such as spatial smoothing and Toeplitz matrix reconstruction have been proposed to decoherence and minimize the DOA estimation error in the MUSIC algorithm. However, these methods can only be applied to uniform linear arrays, which greatly reduces the practicability of the algorithm. This paper proposes to combine a decoherence method with MUSIC algorithm to estimate the azimuth angle (θ) and elevation angle (ϕ) of the source in a planar array which is composed of two orthogonal minimum redundant linear arrays (MRLA). The algorithm is implemented under different Signal-to-Noise Ratio (SNR) and compared with other decoherence methods. Simulation results show the proposed decoherence algorithm can achieve higher DOA estimation accuracy for coherent sources.

AB - The Multiple Signal Classification (MUSIC) algorithm has become a landmark algorithm in the theoretical system of spatial spectrum estimation. This technology has excellent estimation performance and wide application prospects. Accurate Direction of Arrival (DOA) estimation plays a pivotal role in the detection of narrow wave sources. Nevertheless, when the signals are partially correlated or even coherent, the performance of the traditional MUSIC algorithm is greatly reduced. Methods such as spatial smoothing and Toeplitz matrix reconstruction have been proposed to decoherence and minimize the DOA estimation error in the MUSIC algorithm. However, these methods can only be applied to uniform linear arrays, which greatly reduces the practicability of the algorithm. This paper proposes to combine a decoherence method with MUSIC algorithm to estimate the azimuth angle (θ) and elevation angle (ϕ) of the source in a planar array which is composed of two orthogonal minimum redundant linear arrays (MRLA). The algorithm is implemented under different Signal-to-Noise Ratio (SNR) and compared with other decoherence methods. Simulation results show the proposed decoherence algorithm can achieve higher DOA estimation accuracy for coherent sources.

KW - Coherent sources

KW - Direction of arrival

KW - Matrix reconstruction

KW - Minimum redundant linear arrays

KW - Planar array

UR - https://www.scopus.com/pages/publications/85134893752

U2 - 10.1109/PHM2022-London52454.2022.00030

DO - 10.1109/PHM2022-London52454.2022.00030

M3 - Conference contribution

AN - SCOPUS:85134893752

SN - 9781665479554

T3 - Proceedings - 2022 Prognostics and Health Management Conference, PHM-London 2022

SP - 127

EP - 131

BT - Proceedings - 2022 Prognostics and Health Management Conference, PHM-London 2022

A2 - Li, Chuan

A2 - Valentino, Gianluca

A2 - Kang, Ling

A2 - Cabrera, Diego

A2 - Gjorgjevikj, Dejan

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2022 Prognostics and Health Management Conference

Y2 - 27 May 2022 through 29 May 2022

ER -

Zhang H, Zhen D, Zeng F, Feng G, Meng Z, Gu F. Matrix Reconstruction to Estimate Direction of Arrival of Coherent Sources Based on Planar Array. In Li C, Valentino G, Kang L, Cabrera D, Gjorgjevikj D, editors, Proceedings - 2022 Prognostics and Health Management Conference, PHM-London 2022. Institute of Electrical and Electronics Engineers Inc. 2022. p. 127-131. 9808803. (Proceedings - 2022 Prognostics and Health Management Conference, PHM-London 2022). doi: 10.1109/PHM2022-London52454.2022.00030

Matrix Reconstruction to Estimate Direction of Arrival of Coherent Sources Based on Planar Array

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