Random rough surface scattering based on Monte Carlo simulations with the sparse-matrix flat-surface iterative approach

With the advent of modern computers, numerical methods for solving Maxwell's equations are gaining popularity. In the authors' approach, the exact solutions of Maxwell's equations for scattering by a two-dimensional (2D) random rough surface are calculated with a sparse-matrix flat-surface iterative approach/canonical grid (SMFSIA/CAG). Numerical examples are illustrated with up to 131,072 surface unknowns, surface areas between 256 square wavelengths and 1024 square wavelengths, and rms heights of 0.5 wavelength and 1 wavelength. The scattering solution for each surface realization takes less than two CPU minutes for 32768 surface unknowns. Therefore, simulations based on Monte Carlo technique are illustrated with up to 1000 realizations. In this paper, backscattering enhancement of electromagnetic wave scattering from a perfectly conducting 2D random rough surface is studied with Monte Carlo simulations. The numerical simulation results are in excellent agreement with controlled laboratory experiments without adjustable parameters. SMFSLA/CAG has also been extended to the case of electromagnetic wave scattering from 2D dielectric surfaces.