Electromagnetic Wave Modeling for Remote Sensing

Abstract

Presented in this paper is a layer random medium model for fully Polarimetrie remote sensing of geophysical media. The strong permittivity fluctuation theory is used to calculate effective permittivities and the distorted Born approximation is applied to obtain Polarimetrie scattering coefficients. In scattering layers, the embedded scatterers are generally modeled with a non-spherical correlation function with orientation described by a probability density function [1], The model accounts for multiple interactions due to the medium interfaces, coherent effects of wave propagation, first-order cross-polarized return, and multiple scattering to some extent. The paper is composed of five sections. After this introduction, section 2 reviews Polarimetrie scattering descriptions under consideration in terms of scattering coefficients, covariance matrix, and Mueller matrix. Relations between the matrix elements and the scattering coefficients will be shown. Section 3 presents the theoretical model formulated from Maxwell’s equations to derive the Polarimetrie scattering coefficients. Section 4 shows results for some geophysical media such as snow, sea ice, and soybean. Physical insights provided by the theoretical model are used to explain the behaviors of the corresponding covariance matrix and the polarization signatures calculated with Mueller matrix. Finally, section 5 summarizes this paper.