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

Authors

SENEM MAKAL
AHMET KIZILAY

DOI

10.3906/elk-1009-789

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 (x_0, y_0) and the radius (r_p) 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.

Keywords

Electromagnetic scattering, the method of moment, neural network, inverse scattering

First Page

1249

Last Page

1258

Recommended Citation

MAKAL, SENEM and KIZILAY, AHMET (2012) "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 Sciences: Vol. 20: No. 8, Article 3. https://doi.org/10.3906/elk-1009-789
Available at: https://journals.tubitak.gov.tr/elektrik/vol20/iss8/3