Journal Article

FZJ-2024-02306

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Optimizing Sensing Matrices for Spherical Near-Field Antenna Measurements

Bangun, A. (Corresponding author)FZJ* ; Culotta-Lopez, C.

2023
IEEE New York, NY

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Please use a persistent id in citations: doi:10.1109/TAP.2022.3227010  doi:10.34734/FZJ-2024-02306

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.

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Contributing Institute(s):

1. Datenanalyse und Maschinenlernen (IAS-8)

Research Program(s):

1. 5112 - Cross-Domain Algorithms, Tools, Methods Labs (ATMLs) and Research Groups (POF4-511) (POF4-511)

Appears in the scientific report 2024

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Database coverage:
; ; Clarivate Analytics Master Journal List ; Current Contents - Engineering, Computing and Technology ; Ebsco Academic Search ; Essential Science Indicators ; IF >= 5 ; JCR ; SCOPUS ; Science Citation Index Expanded ; Web of Science Core Collection

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