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A Combined Microwave Imaging Algorithm for Localization and Moisture Level Estimation in Multilayered Media

Omrani, Adel ORCID iD icon; Yadav, Rahul; Link, Guido; Vauhkonen, Marko; Lahivaara, Timo; Jelonnek, John

Abstract (englisch):

In this work, a multistatic uniform diffraction tomography (MUDT) method, that was proposed by the authors as a new qualitative imaging method just recently, is combined with the quantitative Bayesian inversion framework. In this combined approach, MUDT is applied to find the location of the moisture and this localization is employed as a pre-knowledge for the Bayesian framework to estimate the moisture levels in a polymer foam. The proposed combined algorithm might become a major part of the development of a new kind of intelligent industrial microwave drying systems. The imaging algorithm is tested with simulated measurement data. The frequency band from 8 GHz to 12 GHz (X-band) is used for the MUDT algorithm whereas a single frequency of 8.2 GHz is assumed for the Bayesian framework. The first results demonstrate the ability of the developed combined algorithm for optimizing the computational load unlike seen in the quantitative inversion approaches.


Postprint §
DOI: 10.5445/IR/1000133456
Veröffentlicht am 13.12.2021
Originalveröffentlichung
DOI: 10.23919/EuCAP51087.2021.9411327
Scopus
Zitationen: 9
Dimensions
Zitationen: 7
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Hochfrequenztechnik und Elektronik (IHE)
Institut für Hochleistungsimpuls- und Mikrowellentechnik (IHM)
Publikationstyp Proceedingsbeitrag
Publikationsmonat/-jahr 03.2021
Sprache Englisch
Identifikator ISBN: 978-88-312-9902-2
KITopen-ID: 1000133456
HGF-Programm 38.03.02 (POF IV, LK 01) Power-based Fuels and Chemicals
Erschienen in 2021 15th European Conference on Antennas and Propagation (EuCAP), 22-26 March 2021, Düsseldorf, Germany
Veranstaltung 15th European Conference on Antennas and Propagation (EuCAP 2021), Online, 22.03.2021 – 26.03.2021
Verlag Institute of Electrical and Electronics Engineers (IEEE)
Projektinformation TOMOCON (EU, H2020, 764902)
Nachgewiesen in Dimensions
Scopus
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