Journals / Turkish Journal of Electrical Engineering and Computer Science / 2012 / Cilt: 20 - Sayı: Sup.2

A neural-based electromagnetic inverse scattering approach to the detection of a conducting cylinder coated with a dielectric material

Pages
1249–1258
Publication Date
2011-12-01
DOI
—
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

This is an application of the electromagnetic inverse scattering of the objects embedded in a material based on the use of a neural network.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:In this study, a radial basis function neural network approach is applied for the estimation of the localization and the radius of a conducting cylinder with a circular cross-section coated with a dielectric material.
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Key Findings & Data:RCS values are obtained using 10 different scattering angles that are fed into the network.
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Conclusion & Impact:This is an application of the electromagnetic inverse scattering of the objects embedded in a material based on the use of a neural network.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Electromagnetic scattering · the method of moment · neural network

Abstract

In this study, a radial basis function neural network approach is applied for the estimation of the localization and the radius of a conducting cylinder with a circular cross-section coated with a dielectric material. A set of features, the radar cross-section (RCS) values, are derived from scattered fields, which are calculated using the surface equivalence principle and the method of moment. RCS values are obtained using 10 different scattering angles that are fed into the network. The outputs of the network are the location (x0, y0) and the radius (rp) of the conducting cylinder. This is an application of the electromagnetic inverse scattering of the objects embedded in a material based on the use of a neural network.

Özet

In this study, a radial basis function neural network approach is applied for the estimation of the localization and the radius of a conducting cylinder with a circular cross-section coated with a dielectric material. A set of features, the radar cross-section (RCS) values, are derived from scattered fields, which are calculated using the surface equivalence principle and the method of moment. RCS values are obtained using 10 different scattering angles that are fed into the network. The outputs of the network are the location (x0, y0) and the radius (rp) of the conducting cylinder. This is an application of the electromagnetic inverse scattering of the objects embedded in a material based on the use of a neural network.

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Cite This Article

MAKAL, S., KIZILAY, A. (2011). A neural-based electromagnetic inverse scattering approach to the detection of a conducting cylinder coated with a dielectric material. Turkish Journal of Electrical Engineering and Computer Science, Cilt: 20 - Sayı: Sup.2, 1249–1258. https://ajindex.com/articles/188973

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