Szczegóły publikacji

Opis bibliograficzny

Multisetup correction of antenna radiation patterns obtained from phaseless nonanechoic measurements / Vorya Waladi, Ilona PIEKARZ, Jakub SOROCKI, Adrian Bekasiewicz // IEEE Antennas and Wireless Propagation Letters ; ISSN  1536-1225 . — 2025 — vol. 24 no. 11, s. 3910-3914. — Bibliogr. s. 3913-3914, Abstr. — Publikacja dostępna online od: 2025-08-07

Autorzy (4)

Słowa kluczowe

nonanechoic measurementsantenna far-field responsespost-processingphaseless datalocal regression

Dane bibliometryczne

ID BaDAP165362
Data dodania do BaDAP2026-01-13
Tekst źródłowyURL
DOI10.1109/LAWP.2025.3596814
Rok publikacji2025
Typ publikacjiartykuł w czasopiśmie
Otwarty dostęptak
Czasopismo/seriaIEEE Antennas and Wireless Propagation Letters

Abstract

Evaluation of antenna radiation patterns is normally performed at professional facilities where strict control over propagation conditions is maintained. Alternatively, experiments can be realized in uncontrolled environments and then corrected to diminish the effects of noise and interference patterns on far-field responses. Existing post-processing methods normally require complex (i.e., magnitude and phase) transmission characteristics that might not be available when low-cost measurement gear is used. In this work, a framework for multisetup correction of far-field radiation patterns based on phaseless data acquired in nonanechoic conditions is presented. The method involves acquisition of frequency responses over a selected bandwidth for a set of spatially separated test setups. The obtained multisetup data are subject to robust smoothing and an appropriate convex combination to retain the refined characteristics. The approach has been demonstrated using a Vivaldi antenna measured for two test configurations and a few frequencies. For the considered experiments, the improvement of radiation patterns’ fidelity due to post-processing is up to 9 dB w.r.t. uncorrected data. The framework has also been benchmarked against the state-of-the-art algorithms in terms of performance.

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