Synthesis of planar sparse arrays by perturbed compressive sampling framework

Recently, compressive sensing (CS) theory has been applied for synthesising maximally sparse arrays, in which the best subset of sampling element locations is chosen to compose a sparse array for matching a desired radiation pattern. However, their performances are strongly depended on the proper se...

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Veröffentlicht in:	IET microwaves, antennas & propagation Jg. 10; H. 11; S. 1146 - 1153
Hauptverfasser:	Yan, Fei, Yang, Peng, Yang, Feng, Dong, Tao
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	The Institution of Engineering and Technology 20.08.2016
Schlagworte:	antenna radiation patterns aperture antennas array signal processing Arrays compressed sensing computational cost reduction continuous array aperture gridding continuous element placement CS theory extended PCS model FOCal under‐determined system solver joint sparse recovery approach Mathematical models Microwave antennas modelling error reduction pattern matching Perturbation methods perturbed compressive sampling framework planar antenna arrays planar sparse array synthesis radiation pattern matching Recovering Sampling secondary grid strategy signal synthesis Solvers Synthesis signal synthesis planar sparse array synthesis pattern matching compressed sensing aperture antennas modelling error reduction joint sparse recovery approach perturbed compressive sampling framework continuous array aperture gridding FOCal under-determined system solver planar antenna arrays extended PCS model radiation pattern matching continuous element placement antenna radiation patterns CS theory computational cost reduction array signal processing secondary grid strategy
ISSN:	1751-8725, 1751-8733
Online-Zugang:	Volltext
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