“Conical” Frustum Multi-Beam Phased Arrays for Air Traffic Control Radars

The design of conical frustum phased array antennas for air traffic control (ATC) radar systems is addressed. The array architecture, which is controlled by a fully digital beam-forming (DBF) network, is composed by a set of equal vertical modules. Each module consists of a linear sparse array that...
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Autor*in:	Paolo Rocca [verfasserIn] Nicola Anselmi [verfasserIn] Mohammad Abdul Hannan [verfasserIn] Andrea Massa [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2022

Schlagwörter:	phased array conical frustum array sparse array multi-beam array digital beamforming compressive sensing

Übergeordnetes Werk:	In: Sensors - MDPI AG, 2003, 22(2022), 19, p 7309
Übergeordnetes Werk:	volume:22 ; year:2022 ; number:19, p 7309

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.3390/s22197309

Katalog-ID:	DOAJ028110366

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spelling	10.3390/s22197309 doi (DE-627)DOAJ028110366 (DE-599)DOAJ219da2a14ed9423e8697cab7600558fb DE-627 ger DE-627 rakwb eng TP1-1185 Paolo Rocca verfasserin aut “Conical” Frustum Multi-Beam Phased Arrays for Air Traffic Control Radars 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The design of conical frustum phased array antennas for air traffic control (ATC) radar systems is addressed. The array architecture, which is controlled by a fully digital beam-forming (DBF) network, is composed by a set of equal vertical modules. Each module consists of a linear sparse array that generates on receive multiple instantaneous beams pointing along different directions in elevation. To reach the best trade-off between the antenna complexity (i.e., minimum number of array elements and/or radio frequency components) and radiation performance (i.e., matching a set of reference patterns), the synthesis problem is formulated in the Compressive Sampling (CS) framework. Then, the positions of the array elements and the complex excitations for generating each single beam are jointly determined through a customized version of the Bayesian CS (BCS) tool. Representative numerical results, concerned with ideal as well as real antenna models, are reported both to validate the proposed design strategy and to assess the effectiveness of the synthesized modular sparse array architecture also in comparison with conventional arrays with uniformly-spaced elements. phased array conical frustum array sparse array multi-beam array digital beamforming compressive sensing Chemical technology Nicola Anselmi verfasserin aut Mohammad Abdul Hannan verfasserin aut Andrea Massa verfasserin aut In Sensors MDPI AG, 2003 22(2022), 19, p 7309 (DE-627)331640910 (DE-600)2052857-7 14248220 nnns volume:22 year:2022 number:19, p 7309 https://doi.org/10.3390/s22197309 kostenfrei https://doaj.org/article/219da2a14ed9423e8697cab7600558fb kostenfrei https://www.mdpi.com/1424-8220/22/19/7309 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 22 2022 19, p 7309
allfields_unstemmed	10.3390/s22197309 doi (DE-627)DOAJ028110366 (DE-599)DOAJ219da2a14ed9423e8697cab7600558fb DE-627 ger DE-627 rakwb eng TP1-1185 Paolo Rocca verfasserin aut “Conical” Frustum Multi-Beam Phased Arrays for Air Traffic Control Radars 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The design of conical frustum phased array antennas for air traffic control (ATC) radar systems is addressed. The array architecture, which is controlled by a fully digital beam-forming (DBF) network, is composed by a set of equal vertical modules. Each module consists of a linear sparse array that generates on receive multiple instantaneous beams pointing along different directions in elevation. To reach the best trade-off between the antenna complexity (i.e., minimum number of array elements and/or radio frequency components) and radiation performance (i.e., matching a set of reference patterns), the synthesis problem is formulated in the Compressive Sampling (CS) framework. Then, the positions of the array elements and the complex excitations for generating each single beam are jointly determined through a customized version of the Bayesian CS (BCS) tool. Representative numerical results, concerned with ideal as well as real antenna models, are reported both to validate the proposed design strategy and to assess the effectiveness of the synthesized modular sparse array architecture also in comparison with conventional arrays with uniformly-spaced elements. phased array conical frustum array sparse array multi-beam array digital beamforming compressive sensing Chemical technology Nicola Anselmi verfasserin aut Mohammad Abdul Hannan verfasserin aut Andrea Massa verfasserin aut In Sensors MDPI AG, 2003 22(2022), 19, p 7309 (DE-627)331640910 (DE-600)2052857-7 14248220 nnns volume:22 year:2022 number:19, p 7309 https://doi.org/10.3390/s22197309 kostenfrei https://doaj.org/article/219da2a14ed9423e8697cab7600558fb kostenfrei https://www.mdpi.com/1424-8220/22/19/7309 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 22 2022 19, p 7309
allfieldsGer	10.3390/s22197309 doi (DE-627)DOAJ028110366 (DE-599)DOAJ219da2a14ed9423e8697cab7600558fb DE-627 ger DE-627 rakwb eng TP1-1185 Paolo Rocca verfasserin aut “Conical” Frustum Multi-Beam Phased Arrays for Air Traffic Control Radars 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The design of conical frustum phased array antennas for air traffic control (ATC) radar systems is addressed. The array architecture, which is controlled by a fully digital beam-forming (DBF) network, is composed by a set of equal vertical modules. Each module consists of a linear sparse array that generates on receive multiple instantaneous beams pointing along different directions in elevation. To reach the best trade-off between the antenna complexity (i.e., minimum number of array elements and/or radio frequency components) and radiation performance (i.e., matching a set of reference patterns), the synthesis problem is formulated in the Compressive Sampling (CS) framework. Then, the positions of the array elements and the complex excitations for generating each single beam are jointly determined through a customized version of the Bayesian CS (BCS) tool. Representative numerical results, concerned with ideal as well as real antenna models, are reported both to validate the proposed design strategy and to assess the effectiveness of the synthesized modular sparse array architecture also in comparison with conventional arrays with uniformly-spaced elements. phased array conical frustum array sparse array multi-beam array digital beamforming compressive sensing Chemical technology Nicola Anselmi verfasserin aut Mohammad Abdul Hannan verfasserin aut Andrea Massa verfasserin aut In Sensors MDPI AG, 2003 22(2022), 19, p 7309 (DE-627)331640910 (DE-600)2052857-7 14248220 nnns volume:22 year:2022 number:19, p 7309 https://doi.org/10.3390/s22197309 kostenfrei https://doaj.org/article/219da2a14ed9423e8697cab7600558fb kostenfrei https://www.mdpi.com/1424-8220/22/19/7309 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 22 2022 19, p 7309
allfieldsSound	10.3390/s22197309 doi (DE-627)DOAJ028110366 (DE-599)DOAJ219da2a14ed9423e8697cab7600558fb DE-627 ger DE-627 rakwb eng TP1-1185 Paolo Rocca verfasserin aut “Conical” Frustum Multi-Beam Phased Arrays for Air Traffic Control Radars 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The design of conical frustum phased array antennas for air traffic control (ATC) radar systems is addressed. The array architecture, which is controlled by a fully digital beam-forming (DBF) network, is composed by a set of equal vertical modules. Each module consists of a linear sparse array that generates on receive multiple instantaneous beams pointing along different directions in elevation. To reach the best trade-off between the antenna complexity (i.e., minimum number of array elements and/or radio frequency components) and radiation performance (i.e., matching a set of reference patterns), the synthesis problem is formulated in the Compressive Sampling (CS) framework. Then, the positions of the array elements and the complex excitations for generating each single beam are jointly determined through a customized version of the Bayesian CS (BCS) tool. Representative numerical results, concerned with ideal as well as real antenna models, are reported both to validate the proposed design strategy and to assess the effectiveness of the synthesized modular sparse array architecture also in comparison with conventional arrays with uniformly-spaced elements. phased array conical frustum array sparse array multi-beam array digital beamforming compressive sensing Chemical technology Nicola Anselmi verfasserin aut Mohammad Abdul Hannan verfasserin aut Andrea Massa verfasserin aut In Sensors MDPI AG, 2003 22(2022), 19, p 7309 (DE-627)331640910 (DE-600)2052857-7 14248220 nnns volume:22 year:2022 number:19, p 7309 https://doi.org/10.3390/s22197309 kostenfrei https://doaj.org/article/219da2a14ed9423e8697cab7600558fb kostenfrei https://www.mdpi.com/1424-8220/22/19/7309 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 22 2022 19, p 7309
language	English
source	In Sensors 22(2022), 19, p 7309 volume:22 year:2022 number:19, p 7309
sourceStr	In Sensors 22(2022), 19, p 7309 volume:22 year:2022 number:19, p 7309
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	phased array conical frustum array sparse array multi-beam array digital beamforming compressive sensing Chemical technology
isfreeaccess_bool	true
container_title	Sensors
authorswithroles_txt_mv	Paolo Rocca @@aut@@ Nicola Anselmi @@aut@@ Mohammad Abdul Hannan @@aut@@ Andrea Massa @@aut@@
publishDateDaySort_date	2022-01-01T00:00:00Z
hierarchy_top_id	331640910
id	DOAJ028110366
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callnumber-first	T - Technology
author	Paolo Rocca
spellingShingle	Paolo Rocca misc TP1-1185 misc phased array misc conical frustum array misc sparse array misc multi-beam array misc digital beamforming misc compressive sensing misc Chemical technology “Conical” Frustum Multi-Beam Phased Arrays for Air Traffic Control Radars
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topic	misc TP1-1185 misc phased array misc conical frustum array misc sparse array misc multi-beam array misc digital beamforming misc compressive sensing misc Chemical technology
topic_unstemmed	misc TP1-1185 misc phased array misc conical frustum array misc sparse array misc multi-beam array misc digital beamforming misc compressive sensing misc Chemical technology
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title	“Conical” Frustum Multi-Beam Phased Arrays for Air Traffic Control Radars
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title_auth	“Conical” Frustum Multi-Beam Phased Arrays for Air Traffic Control Radars
abstract	The design of conical frustum phased array antennas for air traffic control (ATC) radar systems is addressed. The array architecture, which is controlled by a fully digital beam-forming (DBF) network, is composed by a set of equal vertical modules. Each module consists of a linear sparse array that generates on receive multiple instantaneous beams pointing along different directions in elevation. To reach the best trade-off between the antenna complexity (i.e., minimum number of array elements and/or radio frequency components) and radiation performance (i.e., matching a set of reference patterns), the synthesis problem is formulated in the Compressive Sampling (CS) framework. Then, the positions of the array elements and the complex excitations for generating each single beam are jointly determined through a customized version of the Bayesian CS (BCS) tool. Representative numerical results, concerned with ideal as well as real antenna models, are reported both to validate the proposed design strategy and to assess the effectiveness of the synthesized modular sparse array architecture also in comparison with conventional arrays with uniformly-spaced elements.
abstractGer	The design of conical frustum phased array antennas for air traffic control (ATC) radar systems is addressed. The array architecture, which is controlled by a fully digital beam-forming (DBF) network, is composed by a set of equal vertical modules. Each module consists of a linear sparse array that generates on receive multiple instantaneous beams pointing along different directions in elevation. To reach the best trade-off between the antenna complexity (i.e., minimum number of array elements and/or radio frequency components) and radiation performance (i.e., matching a set of reference patterns), the synthesis problem is formulated in the Compressive Sampling (CS) framework. Then, the positions of the array elements and the complex excitations for generating each single beam are jointly determined through a customized version of the Bayesian CS (BCS) tool. Representative numerical results, concerned with ideal as well as real antenna models, are reported both to validate the proposed design strategy and to assess the effectiveness of the synthesized modular sparse array architecture also in comparison with conventional arrays with uniformly-spaced elements.
abstract_unstemmed	The design of conical frustum phased array antennas for air traffic control (ATC) radar systems is addressed. The array architecture, which is controlled by a fully digital beam-forming (DBF) network, is composed by a set of equal vertical modules. Each module consists of a linear sparse array that generates on receive multiple instantaneous beams pointing along different directions in elevation. To reach the best trade-off between the antenna complexity (i.e., minimum number of array elements and/or radio frequency components) and radiation performance (i.e., matching a set of reference patterns), the synthesis problem is formulated in the Compressive Sampling (CS) framework. Then, the positions of the array elements and the complex excitations for generating each single beam are jointly determined through a customized version of the Bayesian CS (BCS) tool. Representative numerical results, concerned with ideal as well as real antenna models, are reported both to validate the proposed design strategy and to assess the effectiveness of the synthesized modular sparse array architecture also in comparison with conventional arrays with uniformly-spaced elements.
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title_short	“Conical” Frustum Multi-Beam Phased Arrays for Air Traffic Control Radars
url	https://doi.org/10.3390/s22197309 https://doaj.org/article/219da2a14ed9423e8697cab7600558fb https://www.mdpi.com/1424-8220/22/19/7309 https://doaj.org/toc/1424-8220
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