Synthesis of Large-Scale Planar Isophoric Sparse Arrays Using Iterative Least Squares With Nonredundant Constraints (ILS-NRC)

Chen, L; Liu, Y; Ban, YL; Yang, S; Jay Guo, Y

Synthesis of Large-Scale Planar Isophoric Sparse Arrays Using Iterative Least Squares With Nonredundant Constraints (ILS-NRC)

Chen, L Liu, Y Ban, YL Yang, S Jay Guo, Y

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Publisher:: IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Publication Type:: Journal Article
Citation:: IEEE Transactions on Antennas and Propagation, 2024, 72, (5), pp. 4232-4245
Issue Date:: 2024-05-01

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Field	Value	Language
dc.contributor.author	Chen, L
dc.contributor.author	Liu, Y
dc.contributor.author	Ban, YL
dc.contributor.author	Yang, S
dc.contributor.author	Jay Guo, Y
dc.date.accessioned	2024-08-07T05:11:57Z
dc.date.available	2024-08-07T05:11:57Z
dc.date.issued	2024-05-01
dc.identifier.citation	IEEE Transactions on Antennas and Propagation, 2024, 72, (5), pp. 4232-4245
dc.identifier.issn	0018-926X
dc.identifier.issn	1558-2221
dc.identifier.uri	http://hdl.handle.net/10453/180281
dc.description.abstract	This article presents a novel method to efficiently synthesize large-scale planar isophoric sparse arrays (ISAs), aiming to achieve low sidelobe levels (SLLs). This method tackles the challenge of layout optimization by framing it as a constrained least squares problem and iteratively refining the solution. To accelerate the synthesis process, two key strategies are implemented. First, the method defines the objective function as minimizing the discrepancy between the resulting array pattern and an adaptive reference pattern. This innovative choice obviates the need for introducing numerous sidelobe constraints, streamlining the optimization problem significantly. Second, the method incorporates a redundancy elimination technique. This technique involves calculating the theoretical limits for the achievable minimum spacing and aperture, allowing for the selective retention of only the nonredundant positional constraints. This step further reduces the optimization's computational complexity. Several numerical examples are conducted for different applications. Comparative studies with the iterative convex optimization method show the proposed method's efficiency advantages. In addition, a full-wave analysis of a microstrip patch antenna array verifies the method's effectiveness in real array cases.
dc.language	English
dc.publisher	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
dc.relation.ispartof	IEEE Transactions on Antennas and Propagation
dc.relation.isbasedon	10.1109/TAP.2024.3375971
dc.rights	info:eu-repo/semantics/restrictedAccess
dc.subject	0906 Electrical and Electronic Engineering, 1005 Communications Technologies
dc.subject.classification	Networking & Telecommunications
dc.subject.classification	4006 Communications engineering
dc.subject.classification	4008 Electrical engineering
dc.subject.classification	4009 Electronics, sensors and digital hardware
dc.title	Synthesis of Large-Scale Planar Isophoric Sparse Arrays Using Iterative Least Squares With Nonredundant Constraints (ILS-NRC)
dc.type	Journal Article
utslib.citation.volume	72
utslib.for	0906 Electrical and Electronic Engineering
utslib.for	1005 Communications Technologies
pubs.organisational-group	University of Technology Sydney
pubs.organisational-group	University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	University of Technology Sydney/Strength - GBDTC - Global Big Data Technologies
pubs.organisational-group	University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
pubs.organisational-group	University of Technology Sydney/All Manual Groups
pubs.organisational-group	University of Technology Sydney/All Manual Groups/Global Big Data Technologies Research Centre (GBDTC)
utslib.copyright.status	in_progress	*
dc.date.updated	2024-08-07T05:11:43Z
pubs.issue	5
pubs.publication-status	Published
pubs.volume	72
utslib.citation.issue	5

Abstract:

This article presents a novel method to efficiently synthesize large-scale planar isophoric sparse arrays (ISAs), aiming to achieve low sidelobe levels (SLLs). This method tackles the challenge of layout optimization by framing it as a constrained least squares problem and iteratively refining the solution. To accelerate the synthesis process, two key strategies are implemented. First, the method defines the objective function as minimizing the discrepancy between the resulting array pattern and an adaptive reference pattern. This innovative choice obviates the need for introducing numerous sidelobe constraints, streamlining the optimization problem significantly. Second, the method incorporates a redundancy elimination technique. This technique involves calculating the theoretical limits for the achievable minimum spacing and aperture, allowing for the selective retention of only the nonredundant positional constraints. This step further reduces the optimization's computational complexity. Several numerical examples are conducted for different applications. Comparative studies with the iterative convex optimization method show the proposed method's efficiency advantages. In addition, a full-wave analysis of a microstrip patch antenna array verifies the method's effectiveness in real array cases.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/180281