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Localization of Dielectric Anomalies with Multi-Monostatic S(11) Using 2D MUSIC Algorithm with Spatial Smoothing

This article demonstrates that the complex value of S(11) of an antenna, acquired in a multi-monostatic configuration, can be used for localization of a dielectric anomaly hidden inside a dielectric background medium when the antenna is placed close (~5 mm) to the geometry. It uses an Inverse Synthe...

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Autores principales: Bilal, Ahmad, Cho, Choon Sik
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9320367/
https://www.ncbi.nlm.nih.gov/pubmed/35890973
http://dx.doi.org/10.3390/s22145293
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author Bilal, Ahmad
Cho, Choon Sik
author_facet Bilal, Ahmad
Cho, Choon Sik
author_sort Bilal, Ahmad
collection PubMed
description This article demonstrates that the complex value of S(11) of an antenna, acquired in a multi-monostatic configuration, can be used for localization of a dielectric anomaly hidden inside a dielectric background medium when the antenna is placed close (~5 mm) to the geometry. It uses an Inverse Synthetic Aperture Radar (ISAR) imaging framework where data is acquired at multiple frequencies and look-angles. Initially, near-field scattering data are used for simulation to validate this methodology since the basic derivation of the Multiple Signal Classification (MUSIC) algorithm is based on the plain wave assumption. Later on, from an applications perspective, data acquisition is performed using an antipodal Vivaldi antenna that has eight constant-width slots on each arm. This antenna operates in a frequency range of 1 to 8.5 GHz and its S(11) is fed to the 2D MUSIC algorithm with spatial smoothing whereas the antenna artifact and background effect are removed by subtracting the average S(11) at each antenna location. Measurements reveal that this methodology gives accurate results with both homogeneous and inhomogeneous backgrounds because the size of data sub-arrays trades between the image noise and resolution, hence reducing the effect of inhomogeneity in the background. In addition to near-field ISAR imaging, this study can be used in the ongoing research on breast tumors and brain stroke detection, among others.
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spelling pubmed-93203672022-07-27 Localization of Dielectric Anomalies with Multi-Monostatic S(11) Using 2D MUSIC Algorithm with Spatial Smoothing Bilal, Ahmad Cho, Choon Sik Sensors (Basel) Article This article demonstrates that the complex value of S(11) of an antenna, acquired in a multi-monostatic configuration, can be used for localization of a dielectric anomaly hidden inside a dielectric background medium when the antenna is placed close (~5 mm) to the geometry. It uses an Inverse Synthetic Aperture Radar (ISAR) imaging framework where data is acquired at multiple frequencies and look-angles. Initially, near-field scattering data are used for simulation to validate this methodology since the basic derivation of the Multiple Signal Classification (MUSIC) algorithm is based on the plain wave assumption. Later on, from an applications perspective, data acquisition is performed using an antipodal Vivaldi antenna that has eight constant-width slots on each arm. This antenna operates in a frequency range of 1 to 8.5 GHz and its S(11) is fed to the 2D MUSIC algorithm with spatial smoothing whereas the antenna artifact and background effect are removed by subtracting the average S(11) at each antenna location. Measurements reveal that this methodology gives accurate results with both homogeneous and inhomogeneous backgrounds because the size of data sub-arrays trades between the image noise and resolution, hence reducing the effect of inhomogeneity in the background. In addition to near-field ISAR imaging, this study can be used in the ongoing research on breast tumors and brain stroke detection, among others. MDPI 2022-07-15 /pmc/articles/PMC9320367/ /pubmed/35890973 http://dx.doi.org/10.3390/s22145293 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Bilal, Ahmad
Cho, Choon Sik
Localization of Dielectric Anomalies with Multi-Monostatic S(11) Using 2D MUSIC Algorithm with Spatial Smoothing
title Localization of Dielectric Anomalies with Multi-Monostatic S(11) Using 2D MUSIC Algorithm with Spatial Smoothing
title_full Localization of Dielectric Anomalies with Multi-Monostatic S(11) Using 2D MUSIC Algorithm with Spatial Smoothing
title_fullStr Localization of Dielectric Anomalies with Multi-Monostatic S(11) Using 2D MUSIC Algorithm with Spatial Smoothing
title_full_unstemmed Localization of Dielectric Anomalies with Multi-Monostatic S(11) Using 2D MUSIC Algorithm with Spatial Smoothing
title_short Localization of Dielectric Anomalies with Multi-Monostatic S(11) Using 2D MUSIC Algorithm with Spatial Smoothing
title_sort localization of dielectric anomalies with multi-monostatic s(11) using 2d music algorithm with spatial smoothing
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9320367/
https://www.ncbi.nlm.nih.gov/pubmed/35890973
http://dx.doi.org/10.3390/s22145293
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