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DOA Estimation Based on Real-Valued Cross Correlation Matrix of Coprime Arrays

A fast direction of arrival (DOA) estimation method using a real-valued cross-correlation matrix (CCM) of coprime subarrays is proposed. Firstly, real-valued CCM with extended aperture is constructed to obtain the signal subspaces corresponding to the two subarrays. By analysing the relationship bet...

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Detalles Bibliográficos
Autores principales: Li, Jianfeng, Wang, Feng, Jiang, Defu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5375924/
https://www.ncbi.nlm.nih.gov/pubmed/28335536
http://dx.doi.org/10.3390/s17030638
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author Li, Jianfeng
Wang, Feng
Jiang, Defu
author_facet Li, Jianfeng
Wang, Feng
Jiang, Defu
author_sort Li, Jianfeng
collection PubMed
description A fast direction of arrival (DOA) estimation method using a real-valued cross-correlation matrix (CCM) of coprime subarrays is proposed. Firstly, real-valued CCM with extended aperture is constructed to obtain the signal subspaces corresponding to the two subarrays. By analysing the relationship between the two subspaces, DOA estimations from the two subarrays are simultaneously obtained with automatic pairing. Finally, unique DOA is determined based on the common results from the two subarrays. Compared to partial spectral search (PSS) method and estimation of signal parameter via rotational invariance (ESPRIT) based method for coprime arrays, the proposed algorithm has lower complexity but achieves better DOA estimation performance and handles more sources. Simulation results verify the effectiveness of the approach.
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spelling pubmed-53759242017-04-10 DOA Estimation Based on Real-Valued Cross Correlation Matrix of Coprime Arrays Li, Jianfeng Wang, Feng Jiang, Defu Sensors (Basel) Article A fast direction of arrival (DOA) estimation method using a real-valued cross-correlation matrix (CCM) of coprime subarrays is proposed. Firstly, real-valued CCM with extended aperture is constructed to obtain the signal subspaces corresponding to the two subarrays. By analysing the relationship between the two subspaces, DOA estimations from the two subarrays are simultaneously obtained with automatic pairing. Finally, unique DOA is determined based on the common results from the two subarrays. Compared to partial spectral search (PSS) method and estimation of signal parameter via rotational invariance (ESPRIT) based method for coprime arrays, the proposed algorithm has lower complexity but achieves better DOA estimation performance and handles more sources. Simulation results verify the effectiveness of the approach. MDPI 2017-03-20 /pmc/articles/PMC5375924/ /pubmed/28335536 http://dx.doi.org/10.3390/s17030638 Text en © 2017 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Li, Jianfeng
Wang, Feng
Jiang, Defu
DOA Estimation Based on Real-Valued Cross Correlation Matrix of Coprime Arrays
title DOA Estimation Based on Real-Valued Cross Correlation Matrix of Coprime Arrays
title_full DOA Estimation Based on Real-Valued Cross Correlation Matrix of Coprime Arrays
title_fullStr DOA Estimation Based on Real-Valued Cross Correlation Matrix of Coprime Arrays
title_full_unstemmed DOA Estimation Based on Real-Valued Cross Correlation Matrix of Coprime Arrays
title_short DOA Estimation Based on Real-Valued Cross Correlation Matrix of Coprime Arrays
title_sort doa estimation based on real-valued cross correlation matrix of coprime arrays
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5375924/
https://www.ncbi.nlm.nih.gov/pubmed/28335536
http://dx.doi.org/10.3390/s17030638
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