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Passive Localization of Mixed Far-Field and Near-Field Sources without Estimating the Number of Sources

This paper presents a novel algorithm for the localization of mixed far-field sources (FFSs) and near-field sources (NFSs) without estimating the source number. Firstly, the algorithm decouples the direction-of-arrival (DOA) estimation from the range estimation by exploiting fourth-order spatial-tem...

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Detalles Bibliográficos
Autores principales: Xie, Jian, Tao, Haihong, Rao, Xuan, Su, Jia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4367388/
https://www.ncbi.nlm.nih.gov/pubmed/25668212
http://dx.doi.org/10.3390/s150203834
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author Xie, Jian
Tao, Haihong
Rao, Xuan
Su, Jia
author_facet Xie, Jian
Tao, Haihong
Rao, Xuan
Su, Jia
author_sort Xie, Jian
collection PubMed
description This paper presents a novel algorithm for the localization of mixed far-field sources (FFSs) and near-field sources (NFSs) without estimating the source number. Firstly, the algorithm decouples the direction-of-arrival (DOA) estimation from the range estimation by exploiting fourth-order spatial-temporal cumulants of the observed data. Based on the joint diagonalization structure of multiple spatial-temporal cumulant matrices, a new one-dimensional (1-D) spatial spectrum function is derived to generate the DOA estimates of both FFSs and NFSs. Then, the FFSs and NFSs are identified and the range parameters of NFSs are determined via beamforming technique. Compared with traditional mixed sources localization algorithms, the proposed algorithm avoids the performance deterioration induced by erroneous source number estimation. Furthermore, it has a higher resolution capability and improves the estimation accuracy. Computer simulations are implemented to verify the effectiveness of the proposed algorithm.
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spelling pubmed-43673882015-04-30 Passive Localization of Mixed Far-Field and Near-Field Sources without Estimating the Number of Sources Xie, Jian Tao, Haihong Rao, Xuan Su, Jia Sensors (Basel) Article This paper presents a novel algorithm for the localization of mixed far-field sources (FFSs) and near-field sources (NFSs) without estimating the source number. Firstly, the algorithm decouples the direction-of-arrival (DOA) estimation from the range estimation by exploiting fourth-order spatial-temporal cumulants of the observed data. Based on the joint diagonalization structure of multiple spatial-temporal cumulant matrices, a new one-dimensional (1-D) spatial spectrum function is derived to generate the DOA estimates of both FFSs and NFSs. Then, the FFSs and NFSs are identified and the range parameters of NFSs are determined via beamforming technique. Compared with traditional mixed sources localization algorithms, the proposed algorithm avoids the performance deterioration induced by erroneous source number estimation. Furthermore, it has a higher resolution capability and improves the estimation accuracy. Computer simulations are implemented to verify the effectiveness of the proposed algorithm. MDPI 2015-02-06 /pmc/articles/PMC4367388/ /pubmed/25668212 http://dx.doi.org/10.3390/s150203834 Text en © 2015 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 license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Xie, Jian
Tao, Haihong
Rao, Xuan
Su, Jia
Passive Localization of Mixed Far-Field and Near-Field Sources without Estimating the Number of Sources
title Passive Localization of Mixed Far-Field and Near-Field Sources without Estimating the Number of Sources
title_full Passive Localization of Mixed Far-Field and Near-Field Sources without Estimating the Number of Sources
title_fullStr Passive Localization of Mixed Far-Field and Near-Field Sources without Estimating the Number of Sources
title_full_unstemmed Passive Localization of Mixed Far-Field and Near-Field Sources without Estimating the Number of Sources
title_short Passive Localization of Mixed Far-Field and Near-Field Sources without Estimating the Number of Sources
title_sort passive localization of mixed far-field and near-field sources without estimating the number of sources
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4367388/
https://www.ncbi.nlm.nih.gov/pubmed/25668212
http://dx.doi.org/10.3390/s150203834
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