A Fast Macromodeling Approach to Efficiently Simulate Inhomogeneous Electromagnetic Surfaces

TL;DR

This paper introduces a fast macromodeling method for simulating complex electromagnetic surfaces, reducing computational effort and memory use while maintaining accuracy, especially for large, inhomogeneous structures.

Contribution

The paper presents a novel macromodeling approach using fictitious surfaces and an acceleration algorithm based on FFT to efficiently simulate large, complex electromagnetic surfaces.

Findings

Significantly faster simulation times compared to commercial solvers

Reduced memory requirements for large surface simulations

Accurate results validated through numerical examples

Abstract

The full-wave simulation of complex electromagnetic surfaces such as reflectarrays and metasurfaces is a challenging problem. In this paper, we present a macromodeling approach to efficiently simulate complex electromagnetic surfaces composed of PEC traces, possibly with fine features, on a finite-sized multilayer dielectric substrate. In our approach, we enclose each element of the structure with a fictitious surface. By applying the equivalence principle on each surface, we derive a macromodel for each element of the array. This macromodel consists of a linear operator that relates the equivalent electric and magnetic current densities introduced on the fictitious surface. Mutual coupling between the elements of the structure is captured by the equivalent current densities in a fully accurate way. The crux of the proposed technique is to solve for equivalent current densities on the fictitious surface instead of directly solving for the actual current densities on the original scatterer. When simulating complex surfaces, this approach leads to fewer unknowns and better conditioning. We also propose a rigorous acceleration algorithm based on the fast Fourier transform to simulate electrically large surfaces. Numerical results demonstrate that the proposed approach is significantly faster and requires less memory than commercial solvers based on the surface integral equation method, while giving accurate results.