Synthesising multiple-pattern sparse linear array with accurate sidelobe control by the extended reweighted L1-norm minimisation

Ma, X; Liu, Y; Da Xu, K; Zhu, C; Liu, QH

Synthesising multiple-pattern sparse linear array with accurate sidelobe control by the extended reweighted L1-norm minimisation

Ma, X Liu, Y

Da Xu, K Zhu, C Liu, QH

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Publication Type:: Journal Article
Citation:: Electronics Letters, 2018, 54 (9), pp. 548 - 550
Issue Date:: 2018-05-03

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Field	Value	Language
dc.contributor.author	Ma, X	en_US
dc.contributor.author	Liu, Y https://orcid.org/0000-0001-5466-0184	en_US
dc.contributor.author	Da Xu, K	en_US
dc.contributor.author	Zhu, C	en_US
dc.contributor.author	Liu, QH	en_US
dc.date.issued	2018-05-03	en_US
dc.identifier.citation	Electronics Letters, 2018, 54 (9), pp. 548 - 550	en_US
dc.identifier.issn	0013-5194	en_US
dc.identifier.uri	http://hdl.handle.net/10453/132468
dc.description.abstract	© The Institution of Engineering and Technology 2018. The problem of synthesising a sparse linear array with multiple patterns is formulated as an extended reweighted ℓ1-norm minimisation with multiple convex constraints. Synthesis results show that the proposed method can find the common sparse element positions with optimised excitations for multiple-pattern requirements, and the mainlobe, sidelobe as well as nulling region for each pattern can be accurately controlled.	en_US
dc.relation.ispartof	Electronics Letters	en_US
dc.relation.isbasedon	10.1049/el.2018.0333	en_US
dc.rights	info:eu-repo/semantics/openAccess
dc.subject.classification	Electrical & Electronic Engineering	en_US
dc.title	Synthesising multiple-pattern sparse linear array with accurate sidelobe control by the extended reweighted L1-norm minimisation	en_US
dc.type	Journal Article
utslib.citation.volume	9	en_US
utslib.citation.volume	54	en_US
utslib.for	0906 Electrical and Electronic Engineering	en_US
utslib.for	0801 Artificial Intelligence and Image Processing	en_US
utslib.for	1005 Communications Technologies	en_US
pubs.embargo.period	Not known	en_US
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/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - GBDTC - Global Big Data Technologies
utslib.copyright.status	open_access	*
pubs.issue	9	en_US
pubs.publication-status	Published	en_US
pubs.volume	54	en_US

Abstract:

© The Institution of Engineering and Technology 2018. The problem of synthesising a sparse linear array with multiple patterns is formulated as an extended reweighted ℓ1-norm minimisation with multiple convex constraints. Synthesis results show that the proposed method can find the common sparse element positions with optimised excitations for multiple-pattern requirements, and the mainlobe, sidelobe as well as nulling region for each pattern can be accurately controlled.

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http://hdl.handle.net/10453/132468