Machine Learning for 2-D Scattering Analysis using Method of Moments

Abstract

Machine learning is used to determine the polynomial regression of the coefficients of surface currents approximation for a curvilinear 2-D scatterer. The training data are obtained using method of moments with higher order basis functions and Galerkin testing procedure. The effect of polynomial regression order to the accuracy of calcualted radar cross-section is explored.