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Cumulant-Based DOA Estimation of Noncircular Signals against Unknown Mutual Coupling

To effectively find the direction of non-circular signals received by a uniform linear array (ULA) in the presence of non-negligible perturbations between array elements, i.e., mutual coupling, in colored noise, a direction of arrival (DOA) estimation approach in the context of high order statistics...

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Autores principales: Wang, Baoping, Zheng, Junhao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7038720/
https://www.ncbi.nlm.nih.gov/pubmed/32041373
http://dx.doi.org/10.3390/s20030878
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author Wang, Baoping
Zheng, Junhao
author_facet Wang, Baoping
Zheng, Junhao
author_sort Wang, Baoping
collection PubMed
description To effectively find the direction of non-circular signals received by a uniform linear array (ULA) in the presence of non-negligible perturbations between array elements, i.e., mutual coupling, in colored noise, a direction of arrival (DOA) estimation approach in the context of high order statistics is proposed in this correspondence. Exploiting the non-circularity hidden behind a certain class of wireless communication signals to build up an augmented cumulant matrix, and carrying out a reformulation of the distorted steering vector to extract the angular information from the unknown mutual coupling, by exploiting the characteristic of mutual coupling, i.e., a limited operating range and an inverse relation of coupling effects to interspace, we develop a MUSIC-like estimator based on the rank-reduction (RARE) technique to directly determine directions of incident signals without mutual coupling compensation. Besides, we provide a solution to the problem of coherency between signals and mutual coupling between sensors co-existing, by selecting a middle sub-array to mitigate the undesirable effects and exploiting the rotation-invariant property to blindly separate the coherent signals into different groups to enhance the degrees of freedom. Compared with the existing robust DOA methods to the unknown mutual coupling under the framework of fourth-order cumulants (FOC), our work takes advantage of the larger virtual array and is able to resolve more signals due to greater degrees of freedom. Additionally, as the effective aperture is virtually extended, the developed estimator can achieve better performance under scenarios with high degree of mutual coupling between two sensors. Simulation results demonstrate the validity and efficiency of the proposed method.
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spelling pubmed-70387202020-03-09 Cumulant-Based DOA Estimation of Noncircular Signals against Unknown Mutual Coupling Wang, Baoping Zheng, Junhao Sensors (Basel) Article To effectively find the direction of non-circular signals received by a uniform linear array (ULA) in the presence of non-negligible perturbations between array elements, i.e., mutual coupling, in colored noise, a direction of arrival (DOA) estimation approach in the context of high order statistics is proposed in this correspondence. Exploiting the non-circularity hidden behind a certain class of wireless communication signals to build up an augmented cumulant matrix, and carrying out a reformulation of the distorted steering vector to extract the angular information from the unknown mutual coupling, by exploiting the characteristic of mutual coupling, i.e., a limited operating range and an inverse relation of coupling effects to interspace, we develop a MUSIC-like estimator based on the rank-reduction (RARE) technique to directly determine directions of incident signals without mutual coupling compensation. Besides, we provide a solution to the problem of coherency between signals and mutual coupling between sensors co-existing, by selecting a middle sub-array to mitigate the undesirable effects and exploiting the rotation-invariant property to blindly separate the coherent signals into different groups to enhance the degrees of freedom. Compared with the existing robust DOA methods to the unknown mutual coupling under the framework of fourth-order cumulants (FOC), our work takes advantage of the larger virtual array and is able to resolve more signals due to greater degrees of freedom. Additionally, as the effective aperture is virtually extended, the developed estimator can achieve better performance under scenarios with high degree of mutual coupling between two sensors. Simulation results demonstrate the validity and efficiency of the proposed method. MDPI 2020-02-06 /pmc/articles/PMC7038720/ /pubmed/32041373 http://dx.doi.org/10.3390/s20030878 Text en © 2020 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
Wang, Baoping
Zheng, Junhao
Cumulant-Based DOA Estimation of Noncircular Signals against Unknown Mutual Coupling
title Cumulant-Based DOA Estimation of Noncircular Signals against Unknown Mutual Coupling
title_full Cumulant-Based DOA Estimation of Noncircular Signals against Unknown Mutual Coupling
title_fullStr Cumulant-Based DOA Estimation of Noncircular Signals against Unknown Mutual Coupling
title_full_unstemmed Cumulant-Based DOA Estimation of Noncircular Signals against Unknown Mutual Coupling
title_short Cumulant-Based DOA Estimation of Noncircular Signals against Unknown Mutual Coupling
title_sort cumulant-based doa estimation of noncircular signals against unknown mutual coupling
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7038720/
https://www.ncbi.nlm.nih.gov/pubmed/32041373
http://dx.doi.org/10.3390/s20030878
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