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@ARTICLE{Bangun:1024633,
author = {Bangun, Arya and Culotta-Lopez, Cosme},
title = {{O}ptimizing {S}ensing {M}atrices for {S}pherical
{N}ear-{F}ield {A}ntenna {M}easurements},
journal = {IEEE transactions on antennas and propagation},
volume = {71},
number = {2},
issn = {0018-926X},
address = {New York, NY},
publisher = {IEEE},
reportid = {FZJ-2024-02306},
pages = {1716 - 1724},
year = {2023},
abstract = {In this article, we address the problem of reducingthe
number of required samples for spherical near-field(SNF)
antenna measurements by using compressed sensing (CS).A
condition to ensure the numerical performance of
sparserecovery algorithms is the design of a sensing matrix
with lowmutual coherence. Without fixing any part of the
samplingpattern, we directly find sampling points that
minimize themutual coherence of the respective sensing
matrix. Numericalexperiments show that the proposed sampling
scheme yields ahigher recovery success in terms of phase
transition diagramwhen compared to other known sampling
patterns, such asthe spiral and Hammersley sampling schemes.
Furthermore, wealso demonstrate that the application of CS
with an optimizedsensing matrix requires fewer samples than
classical approachesto reconstruct the spherical mode
coefficients (SMCs) and farfieldpattern.Index
Terms—Compressed sensing (CS), near-field to
far-fieldtransformation (NFFFT), optimization, spherical
near-field (SNF)antenna measurements.},
cin = {IAS-8},
ddc = {620},
cid = {I:(DE-Juel1)IAS-8-20210421},
pnm = {5112 - Cross-Domain Algorithms, Tools, Methods Labs (ATMLs)
and Research Groups (POF4-511)},
pid = {G:(DE-HGF)POF4-5112},
typ = {PUB:(DE-HGF)16},
UT = {WOS:000965610700001},
doi = {10.1109/TAP.2022.3227010},
url = {https://juser.fz-juelich.de/record/1024633},
}