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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Autor*in:	Jian Xie [verfasserIn] Haihong Tao [verfasserIn] Xuan Rao [verfasserIn] Jia Su [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2015

Schlagwörter:	sensor array signal processing DOA estimation far-field near-field source localization range estimation fourth-order cumulants

Übergeordnetes Werk:	In: Sensors - MDPI AG, 2003, 15(2015), 2, Seite 3834-3853
Übergeordnetes Werk:	volume:15 ; year:2015 ; number:2 ; pages:3834-3853

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.3390/s150203834

Katalog-ID:	DOAJ031638074

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520			\|a 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.
650		4	\|a sensor array signal processing
650		4	\|a DOA estimation
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650		4	\|a near-field
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650		4	\|a range estimation
650		4	\|a fourth-order cumulants
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allfields	10.3390/s150203834 doi (DE-627)DOAJ031638074 (DE-599)DOAJ440fe669757c4ecc89792a951d1198fa DE-627 ger DE-627 rakwb eng TP1-1185 Jian Xie verfasserin aut Passive Localization of Mixed Far-Field and Near-Field Sources without Estimating the Number of Sources 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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. sensor array signal processing DOA estimation far-field near-field source localization range estimation fourth-order cumulants Chemical technology Haihong Tao verfasserin aut Xuan Rao verfasserin aut Jia Su verfasserin aut In Sensors MDPI AG, 2003 15(2015), 2, Seite 3834-3853 (DE-627)331640910 (DE-600)2052857-7 14248220 nnns volume:15 year:2015 number:2 pages:3834-3853 https://doi.org/10.3390/s150203834 kostenfrei https://doaj.org/article/440fe669757c4ecc89792a951d1198fa kostenfrei http://www.mdpi.com/1424-8220/15/2/3834 kostenfrei https://doaj.org/toc/1424-8220 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2111 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 15 2015 2 3834-3853
spelling	10.3390/s150203834 doi (DE-627)DOAJ031638074 (DE-599)DOAJ440fe669757c4ecc89792a951d1198fa DE-627 ger DE-627 rakwb eng TP1-1185 Jian Xie verfasserin aut Passive Localization of Mixed Far-Field and Near-Field Sources without Estimating the Number of Sources 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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. sensor array signal processing DOA estimation far-field near-field source localization range estimation fourth-order cumulants Chemical technology Haihong Tao verfasserin aut Xuan Rao verfasserin aut Jia Su verfasserin aut In Sensors MDPI AG, 2003 15(2015), 2, Seite 3834-3853 (DE-627)331640910 (DE-600)2052857-7 14248220 nnns volume:15 year:2015 number:2 pages:3834-3853 https://doi.org/10.3390/s150203834 kostenfrei https://doaj.org/article/440fe669757c4ecc89792a951d1198fa kostenfrei http://www.mdpi.com/1424-8220/15/2/3834 kostenfrei https://doaj.org/toc/1424-8220 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2111 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 15 2015 2 3834-3853
allfields_unstemmed	10.3390/s150203834 doi (DE-627)DOAJ031638074 (DE-599)DOAJ440fe669757c4ecc89792a951d1198fa DE-627 ger DE-627 rakwb eng TP1-1185 Jian Xie verfasserin aut Passive Localization of Mixed Far-Field and Near-Field Sources without Estimating the Number of Sources 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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. sensor array signal processing DOA estimation far-field near-field source localization range estimation fourth-order cumulants Chemical technology Haihong Tao verfasserin aut Xuan Rao verfasserin aut Jia Su verfasserin aut In Sensors MDPI AG, 2003 15(2015), 2, Seite 3834-3853 (DE-627)331640910 (DE-600)2052857-7 14248220 nnns volume:15 year:2015 number:2 pages:3834-3853 https://doi.org/10.3390/s150203834 kostenfrei https://doaj.org/article/440fe669757c4ecc89792a951d1198fa kostenfrei http://www.mdpi.com/1424-8220/15/2/3834 kostenfrei https://doaj.org/toc/1424-8220 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2111 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 15 2015 2 3834-3853
allfieldsGer	10.3390/s150203834 doi (DE-627)DOAJ031638074 (DE-599)DOAJ440fe669757c4ecc89792a951d1198fa DE-627 ger DE-627 rakwb eng TP1-1185 Jian Xie verfasserin aut Passive Localization of Mixed Far-Field and Near-Field Sources without Estimating the Number of Sources 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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. sensor array signal processing DOA estimation far-field near-field source localization range estimation fourth-order cumulants Chemical technology Haihong Tao verfasserin aut Xuan Rao verfasserin aut Jia Su verfasserin aut In Sensors MDPI AG, 2003 15(2015), 2, Seite 3834-3853 (DE-627)331640910 (DE-600)2052857-7 14248220 nnns volume:15 year:2015 number:2 pages:3834-3853 https://doi.org/10.3390/s150203834 kostenfrei https://doaj.org/article/440fe669757c4ecc89792a951d1198fa kostenfrei http://www.mdpi.com/1424-8220/15/2/3834 kostenfrei https://doaj.org/toc/1424-8220 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2111 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 15 2015 2 3834-3853
allfieldsSound	10.3390/s150203834 doi (DE-627)DOAJ031638074 (DE-599)DOAJ440fe669757c4ecc89792a951d1198fa DE-627 ger DE-627 rakwb eng TP1-1185 Jian Xie verfasserin aut Passive Localization of Mixed Far-Field and Near-Field Sources without Estimating the Number of Sources 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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. sensor array signal processing DOA estimation far-field near-field source localization range estimation fourth-order cumulants Chemical technology Haihong Tao verfasserin aut Xuan Rao verfasserin aut Jia Su verfasserin aut In Sensors MDPI AG, 2003 15(2015), 2, Seite 3834-3853 (DE-627)331640910 (DE-600)2052857-7 14248220 nnns volume:15 year:2015 number:2 pages:3834-3853 https://doi.org/10.3390/s150203834 kostenfrei https://doaj.org/article/440fe669757c4ecc89792a951d1198fa kostenfrei http://www.mdpi.com/1424-8220/15/2/3834 kostenfrei https://doaj.org/toc/1424-8220 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2111 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 15 2015 2 3834-3853
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source	In Sensors 15(2015), 2, Seite 3834-3853 volume:15 year:2015 number:2 pages:3834-3853
sourceStr	In Sensors 15(2015), 2, Seite 3834-3853 volume:15 year:2015 number:2 pages:3834-3853
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topic_facet	sensor array signal processing DOA estimation far-field near-field source localization range estimation fourth-order cumulants Chemical technology
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container_title	Sensors
authorswithroles_txt_mv	Jian Xie @@aut@@ Haihong Tao @@aut@@ Xuan Rao @@aut@@ Jia Su @@aut@@
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callnumber-first	T - Technology
author	Jian Xie
spellingShingle	Jian Xie misc TP1-1185 misc sensor array signal processing misc DOA estimation misc far-field misc near-field misc source localization misc range estimation misc fourth-order cumulants misc Chemical technology Passive Localization of Mixed Far-Field and Near-Field Sources without Estimating the Number of Sources
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topic_title	TP1-1185 Passive Localization of Mixed Far-Field and Near-Field Sources without Estimating the Number of Sources sensor array signal processing DOA estimation far-field near-field source localization range estimation fourth-order cumulants
topic	misc TP1-1185 misc sensor array signal processing misc DOA estimation misc far-field misc near-field misc source localization misc range estimation misc fourth-order cumulants misc Chemical technology
topic_unstemmed	misc TP1-1185 misc sensor array signal processing misc DOA estimation misc far-field misc near-field misc source localization misc range estimation misc fourth-order cumulants misc Chemical technology
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title	Passive Localization of Mixed Far-Field and Near-Field Sources without Estimating the Number of Sources
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title_sort	passive localization of mixed far-field and near-field sources without estimating the number of sources
callnumber	TP1-1185
title_auth	Passive Localization of Mixed Far-Field and Near-Field Sources without Estimating the Number of Sources
abstract	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.
abstractGer	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.
abstract_unstemmed	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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title_short	Passive Localization of Mixed Far-Field and Near-Field Sources without Estimating the Number of Sources
url	https://doi.org/10.3390/s150203834 https://doaj.org/article/440fe669757c4ecc89792a951d1198fa http://www.mdpi.com/1424-8220/15/2/3834 https://doaj.org/toc/1424-8220
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