Antenna Array Aperture Resource Management of Opportunistic Array Radar for Multiple Target Tracking

In this paper, an antenna array aperture resource management scheme of opportunistic array radar (OAR) based on chance-constraint programming (CCP) is proposed for multiple target tracking (MTT). In the multi-target tracking scenario, multiple beams need to be synthesized to illuminate the targets....
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Qinghua Han [verfasserIn] Yuanshi Zhang [verfasserIn] Zhen Yang [verfasserIn] Weijun Long [verfasserIn] Zhiheng Liang [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2020

Schlagwörter:	Antenna array aperture resource management Bayesian Cramér-Rao lower bound (BCRLB) chance-constraint programming (CCP) opportunistic array radar (OAR)

Übergeordnetes Werk:	In: IEEE Access - IEEE, 2014, 8(2020), Seite 228357-228368
Übergeordnetes Werk:	volume:8 ; year:2020 ; pages:228357-228368

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.1109/ACCESS.2020.3044662

Katalog-ID:	DOAJ056925808

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520			\|a In this paper, an antenna array aperture resource management scheme of opportunistic array radar (OAR) based on chance-constraint programming (CCP) is proposed for multiple target tracking (MTT). In the multi-target tracking scenario, multiple beams need to be synthesized to illuminate the targets. According to the predicted distance of targets, the OAR can intelligently segment the antenna array aperture, and select the optimal combination of array elements to synthesize the satisfactory beams with the element-level antenna steering. Owing to the unique array arrangement and work mode of opportunistic array, the element number in working modes is uncertain. To represent the uncertainty, a fuzzy CCP model is introduced. The element number in working modes is viewed as a fuzzy variable. The maximum tracking error, which is denoted by Bayesian Crameŕ-Rao lower bound(BCRLB), of the targets is regarded as the objective function. The fuzzy simulation algorithm is embedded into genetic algorithm (GA) to compose a hybrid intelligent optimization algorithm to solve the CCP problem. The simulation results verify the validity and practicability of the antenna array aperture resource allocation scheme.
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allfields	10.1109/ACCESS.2020.3044662 doi (DE-627)DOAJ056925808 (DE-599)DOAJ975d5056806340f79862e352111ebb6c DE-627 ger DE-627 rakwb eng TK1-9971 Qinghua Han verfasserin aut Antenna Array Aperture Resource Management of Opportunistic Array Radar for Multiple Target Tracking 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In this paper, an antenna array aperture resource management scheme of opportunistic array radar (OAR) based on chance-constraint programming (CCP) is proposed for multiple target tracking (MTT). In the multi-target tracking scenario, multiple beams need to be synthesized to illuminate the targets. According to the predicted distance of targets, the OAR can intelligently segment the antenna array aperture, and select the optimal combination of array elements to synthesize the satisfactory beams with the element-level antenna steering. Owing to the unique array arrangement and work mode of opportunistic array, the element number in working modes is uncertain. To represent the uncertainty, a fuzzy CCP model is introduced. The element number in working modes is viewed as a fuzzy variable. The maximum tracking error, which is denoted by Bayesian Crameŕ-Rao lower bound(BCRLB), of the targets is regarded as the objective function. The fuzzy simulation algorithm is embedded into genetic algorithm (GA) to compose a hybrid intelligent optimization algorithm to solve the CCP problem. The simulation results verify the validity and practicability of the antenna array aperture resource allocation scheme. Antenna array aperture resource management Bayesian Cramér-Rao lower bound (BCRLB) chance-constraint programming (CCP) opportunistic array radar (OAR) Electrical engineering. Electronics. Nuclear engineering Yuanshi Zhang verfasserin aut Zhen Yang verfasserin aut Weijun Long verfasserin aut Zhiheng Liang verfasserin aut In IEEE Access IEEE, 2014 8(2020), Seite 228357-228368 (DE-627)728440385 (DE-600)2687964-5 21693536 nnns volume:8 year:2020 pages:228357-228368 https://doi.org/10.1109/ACCESS.2020.3044662 kostenfrei https://doaj.org/article/975d5056806340f79862e352111ebb6c kostenfrei https://ieeexplore.ieee.org/document/9293276/ kostenfrei https://doaj.org/toc/2169-3536 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 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_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 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 8 2020 228357-228368
spelling	10.1109/ACCESS.2020.3044662 doi (DE-627)DOAJ056925808 (DE-599)DOAJ975d5056806340f79862e352111ebb6c DE-627 ger DE-627 rakwb eng TK1-9971 Qinghua Han verfasserin aut Antenna Array Aperture Resource Management of Opportunistic Array Radar for Multiple Target Tracking 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In this paper, an antenna array aperture resource management scheme of opportunistic array radar (OAR) based on chance-constraint programming (CCP) is proposed for multiple target tracking (MTT). In the multi-target tracking scenario, multiple beams need to be synthesized to illuminate the targets. According to the predicted distance of targets, the OAR can intelligently segment the antenna array aperture, and select the optimal combination of array elements to synthesize the satisfactory beams with the element-level antenna steering. Owing to the unique array arrangement and work mode of opportunistic array, the element number in working modes is uncertain. To represent the uncertainty, a fuzzy CCP model is introduced. The element number in working modes is viewed as a fuzzy variable. The maximum tracking error, which is denoted by Bayesian Crameŕ-Rao lower bound(BCRLB), of the targets is regarded as the objective function. The fuzzy simulation algorithm is embedded into genetic algorithm (GA) to compose a hybrid intelligent optimization algorithm to solve the CCP problem. The simulation results verify the validity and practicability of the antenna array aperture resource allocation scheme. Antenna array aperture resource management Bayesian Cramér-Rao lower bound (BCRLB) chance-constraint programming (CCP) opportunistic array radar (OAR) Electrical engineering. Electronics. Nuclear engineering Yuanshi Zhang verfasserin aut Zhen Yang verfasserin aut Weijun Long verfasserin aut Zhiheng Liang verfasserin aut In IEEE Access IEEE, 2014 8(2020), Seite 228357-228368 (DE-627)728440385 (DE-600)2687964-5 21693536 nnns volume:8 year:2020 pages:228357-228368 https://doi.org/10.1109/ACCESS.2020.3044662 kostenfrei https://doaj.org/article/975d5056806340f79862e352111ebb6c kostenfrei https://ieeexplore.ieee.org/document/9293276/ kostenfrei https://doaj.org/toc/2169-3536 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 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_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 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 8 2020 228357-228368
allfields_unstemmed	10.1109/ACCESS.2020.3044662 doi (DE-627)DOAJ056925808 (DE-599)DOAJ975d5056806340f79862e352111ebb6c DE-627 ger DE-627 rakwb eng TK1-9971 Qinghua Han verfasserin aut Antenna Array Aperture Resource Management of Opportunistic Array Radar for Multiple Target Tracking 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In this paper, an antenna array aperture resource management scheme of opportunistic array radar (OAR) based on chance-constraint programming (CCP) is proposed for multiple target tracking (MTT). In the multi-target tracking scenario, multiple beams need to be synthesized to illuminate the targets. According to the predicted distance of targets, the OAR can intelligently segment the antenna array aperture, and select the optimal combination of array elements to synthesize the satisfactory beams with the element-level antenna steering. Owing to the unique array arrangement and work mode of opportunistic array, the element number in working modes is uncertain. To represent the uncertainty, a fuzzy CCP model is introduced. The element number in working modes is viewed as a fuzzy variable. The maximum tracking error, which is denoted by Bayesian Crameŕ-Rao lower bound(BCRLB), of the targets is regarded as the objective function. The fuzzy simulation algorithm is embedded into genetic algorithm (GA) to compose a hybrid intelligent optimization algorithm to solve the CCP problem. The simulation results verify the validity and practicability of the antenna array aperture resource allocation scheme. Antenna array aperture resource management Bayesian Cramér-Rao lower bound (BCRLB) chance-constraint programming (CCP) opportunistic array radar (OAR) Electrical engineering. Electronics. Nuclear engineering Yuanshi Zhang verfasserin aut Zhen Yang verfasserin aut Weijun Long verfasserin aut Zhiheng Liang verfasserin aut In IEEE Access IEEE, 2014 8(2020), Seite 228357-228368 (DE-627)728440385 (DE-600)2687964-5 21693536 nnns volume:8 year:2020 pages:228357-228368 https://doi.org/10.1109/ACCESS.2020.3044662 kostenfrei https://doaj.org/article/975d5056806340f79862e352111ebb6c kostenfrei https://ieeexplore.ieee.org/document/9293276/ kostenfrei https://doaj.org/toc/2169-3536 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 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_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 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 8 2020 228357-228368
allfieldsGer	10.1109/ACCESS.2020.3044662 doi (DE-627)DOAJ056925808 (DE-599)DOAJ975d5056806340f79862e352111ebb6c DE-627 ger DE-627 rakwb eng TK1-9971 Qinghua Han verfasserin aut Antenna Array Aperture Resource Management of Opportunistic Array Radar for Multiple Target Tracking 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In this paper, an antenna array aperture resource management scheme of opportunistic array radar (OAR) based on chance-constraint programming (CCP) is proposed for multiple target tracking (MTT). In the multi-target tracking scenario, multiple beams need to be synthesized to illuminate the targets. According to the predicted distance of targets, the OAR can intelligently segment the antenna array aperture, and select the optimal combination of array elements to synthesize the satisfactory beams with the element-level antenna steering. Owing to the unique array arrangement and work mode of opportunistic array, the element number in working modes is uncertain. To represent the uncertainty, a fuzzy CCP model is introduced. The element number in working modes is viewed as a fuzzy variable. The maximum tracking error, which is denoted by Bayesian Crameŕ-Rao lower bound(BCRLB), of the targets is regarded as the objective function. The fuzzy simulation algorithm is embedded into genetic algorithm (GA) to compose a hybrid intelligent optimization algorithm to solve the CCP problem. The simulation results verify the validity and practicability of the antenna array aperture resource allocation scheme. Antenna array aperture resource management Bayesian Cramér-Rao lower bound (BCRLB) chance-constraint programming (CCP) opportunistic array radar (OAR) Electrical engineering. Electronics. Nuclear engineering Yuanshi Zhang verfasserin aut Zhen Yang verfasserin aut Weijun Long verfasserin aut Zhiheng Liang verfasserin aut In IEEE Access IEEE, 2014 8(2020), Seite 228357-228368 (DE-627)728440385 (DE-600)2687964-5 21693536 nnns volume:8 year:2020 pages:228357-228368 https://doi.org/10.1109/ACCESS.2020.3044662 kostenfrei https://doaj.org/article/975d5056806340f79862e352111ebb6c kostenfrei https://ieeexplore.ieee.org/document/9293276/ kostenfrei https://doaj.org/toc/2169-3536 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 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_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 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 8 2020 228357-228368
allfieldsSound	10.1109/ACCESS.2020.3044662 doi (DE-627)DOAJ056925808 (DE-599)DOAJ975d5056806340f79862e352111ebb6c DE-627 ger DE-627 rakwb eng TK1-9971 Qinghua Han verfasserin aut Antenna Array Aperture Resource Management of Opportunistic Array Radar for Multiple Target Tracking 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In this paper, an antenna array aperture resource management scheme of opportunistic array radar (OAR) based on chance-constraint programming (CCP) is proposed for multiple target tracking (MTT). In the multi-target tracking scenario, multiple beams need to be synthesized to illuminate the targets. According to the predicted distance of targets, the OAR can intelligently segment the antenna array aperture, and select the optimal combination of array elements to synthesize the satisfactory beams with the element-level antenna steering. Owing to the unique array arrangement and work mode of opportunistic array, the element number in working modes is uncertain. To represent the uncertainty, a fuzzy CCP model is introduced. The element number in working modes is viewed as a fuzzy variable. The maximum tracking error, which is denoted by Bayesian Crameŕ-Rao lower bound(BCRLB), of the targets is regarded as the objective function. The fuzzy simulation algorithm is embedded into genetic algorithm (GA) to compose a hybrid intelligent optimization algorithm to solve the CCP problem. The simulation results verify the validity and practicability of the antenna array aperture resource allocation scheme. Antenna array aperture resource management Bayesian Cramér-Rao lower bound (BCRLB) chance-constraint programming (CCP) opportunistic array radar (OAR) Electrical engineering. Electronics. Nuclear engineering Yuanshi Zhang verfasserin aut Zhen Yang verfasserin aut Weijun Long verfasserin aut Zhiheng Liang verfasserin aut In IEEE Access IEEE, 2014 8(2020), Seite 228357-228368 (DE-627)728440385 (DE-600)2687964-5 21693536 nnns volume:8 year:2020 pages:228357-228368 https://doi.org/10.1109/ACCESS.2020.3044662 kostenfrei https://doaj.org/article/975d5056806340f79862e352111ebb6c kostenfrei https://ieeexplore.ieee.org/document/9293276/ kostenfrei https://doaj.org/toc/2169-3536 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 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_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 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 8 2020 228357-228368
language	English
source	In IEEE Access 8(2020), Seite 228357-228368 volume:8 year:2020 pages:228357-228368
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topic_facet	Antenna array aperture resource management Bayesian Cramér-Rao lower bound (BCRLB) chance-constraint programming (CCP) opportunistic array radar (OAR) Electrical engineering. Electronics. Nuclear engineering
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authorswithroles_txt_mv	Qinghua Han @@aut@@ Yuanshi Zhang @@aut@@ Zhen Yang @@aut@@ Weijun Long @@aut@@ Zhiheng Liang @@aut@@
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callnumber-first	T - Technology
author	Qinghua Han
spellingShingle	Qinghua Han misc TK1-9971 misc Antenna array aperture resource management misc Bayesian Cramér-Rao lower bound (BCRLB) misc chance-constraint programming (CCP) misc opportunistic array radar (OAR) misc Electrical engineering. Electronics. Nuclear engineering Antenna Array Aperture Resource Management of Opportunistic Array Radar for Multiple Target Tracking
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topic_title	TK1-9971 Antenna Array Aperture Resource Management of Opportunistic Array Radar for Multiple Target Tracking Antenna array aperture resource management Bayesian Cramér-Rao lower bound (BCRLB) chance-constraint programming (CCP) opportunistic array radar (OAR)
topic	misc TK1-9971 misc Antenna array aperture resource management misc Bayesian Cramér-Rao lower bound (BCRLB) misc chance-constraint programming (CCP) misc opportunistic array radar (OAR) misc Electrical engineering. Electronics. Nuclear engineering
topic_unstemmed	misc TK1-9971 misc Antenna array aperture resource management misc Bayesian Cramér-Rao lower bound (BCRLB) misc chance-constraint programming (CCP) misc opportunistic array radar (OAR) misc Electrical engineering. Electronics. Nuclear engineering
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title	Antenna Array Aperture Resource Management of Opportunistic Array Radar for Multiple Target Tracking
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title_sort	antenna array aperture resource management of opportunistic array radar for multiple target tracking
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title_auth	Antenna Array Aperture Resource Management of Opportunistic Array Radar for Multiple Target Tracking
abstract	In this paper, an antenna array aperture resource management scheme of opportunistic array radar (OAR) based on chance-constraint programming (CCP) is proposed for multiple target tracking (MTT). In the multi-target tracking scenario, multiple beams need to be synthesized to illuminate the targets. According to the predicted distance of targets, the OAR can intelligently segment the antenna array aperture, and select the optimal combination of array elements to synthesize the satisfactory beams with the element-level antenna steering. Owing to the unique array arrangement and work mode of opportunistic array, the element number in working modes is uncertain. To represent the uncertainty, a fuzzy CCP model is introduced. The element number in working modes is viewed as a fuzzy variable. The maximum tracking error, which is denoted by Bayesian Crameŕ-Rao lower bound(BCRLB), of the targets is regarded as the objective function. The fuzzy simulation algorithm is embedded into genetic algorithm (GA) to compose a hybrid intelligent optimization algorithm to solve the CCP problem. The simulation results verify the validity and practicability of the antenna array aperture resource allocation scheme.
abstractGer	In this paper, an antenna array aperture resource management scheme of opportunistic array radar (OAR) based on chance-constraint programming (CCP) is proposed for multiple target tracking (MTT). In the multi-target tracking scenario, multiple beams need to be synthesized to illuminate the targets. According to the predicted distance of targets, the OAR can intelligently segment the antenna array aperture, and select the optimal combination of array elements to synthesize the satisfactory beams with the element-level antenna steering. Owing to the unique array arrangement and work mode of opportunistic array, the element number in working modes is uncertain. To represent the uncertainty, a fuzzy CCP model is introduced. The element number in working modes is viewed as a fuzzy variable. The maximum tracking error, which is denoted by Bayesian Crameŕ-Rao lower bound(BCRLB), of the targets is regarded as the objective function. The fuzzy simulation algorithm is embedded into genetic algorithm (GA) to compose a hybrid intelligent optimization algorithm to solve the CCP problem. The simulation results verify the validity and practicability of the antenna array aperture resource allocation scheme.
abstract_unstemmed	In this paper, an antenna array aperture resource management scheme of opportunistic array radar (OAR) based on chance-constraint programming (CCP) is proposed for multiple target tracking (MTT). In the multi-target tracking scenario, multiple beams need to be synthesized to illuminate the targets. According to the predicted distance of targets, the OAR can intelligently segment the antenna array aperture, and select the optimal combination of array elements to synthesize the satisfactory beams with the element-level antenna steering. Owing to the unique array arrangement and work mode of opportunistic array, the element number in working modes is uncertain. To represent the uncertainty, a fuzzy CCP model is introduced. The element number in working modes is viewed as a fuzzy variable. The maximum tracking error, which is denoted by Bayesian Crameŕ-Rao lower bound(BCRLB), of the targets is regarded as the objective function. The fuzzy simulation algorithm is embedded into genetic algorithm (GA) to compose a hybrid intelligent optimization algorithm to solve the CCP problem. The simulation results verify the validity and practicability of the antenna array aperture resource allocation scheme.
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title_short	Antenna Array Aperture Resource Management of Opportunistic Array Radar for Multiple Target Tracking
url	https://doi.org/10.1109/ACCESS.2020.3044662 https://doaj.org/article/975d5056806340f79862e352111ebb6c https://ieeexplore.ieee.org/document/9293276/ https://doaj.org/toc/2169-3536
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