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Full-Wave Electromagnetic Scattering From Rough Surfaces With Buried Inhomogeneities.

Authors :
Duan, Xueyang
Moghaddam, Mahta
Source :
IEEE Transactions on Geoscience & Remote Sensing. Jun2017, Vol. 55 Issue 6, p3338-3353. 16p.
Publication Year :
2017

Abstract

We develop a methodology for modeling coherent electromagnetic scattering from rough surfaces with buried inhomogeneities in three dimensions. The inhomogeneities considered in this paper include random spherical media, random cylindrical media, and root-like cylindrical clusters. They are used to simulate rocks, ice particles, and vegetation roots buried beneath the ground surface that can be seen by the low-frequency radars in Earth remote sensing applications. The approach we develop first calculates volumetric scattering from the media using coherent approaches, including both the conventional recursive transition matrix (T-matrix) method as well as a new generalized iterative extended boundary condition method we developed for tilted finite cylinders, and then transforms the T-matrix to the scattering matrix, which is then used to form the full scattered field of layered structures with rough surface and subsurfaces. We validate the methodology by comparing with other numerical solutions for special cases, and show sensitivity results for scattering from rough surface with buried random spherical media and random cylindrical media of different densities. We also construct a basic root model and calculate the scattering cross sections from single and multiple root clusters with or without a subsurface interface underneath. With the approach developed in this paper, we are able to study the sensitivity of radar signals to subsurface scatterers. For example, our simulations show that, depending on their density and water content, buried roots could enhance the backscatter from a single rough surface by as much as 5 dB in co-pol components, and substantially more in cross-pol components. The results of this model are expected to enable more accurate geophysical retrievals of soil moisture as well as soil organic content. [ABSTRACT FROM PUBLISHER]

Details

Language :
English
ISSN :
01962892
Volume :
55
Issue :
6
Database :
Academic Search Index
Journal :
IEEE Transactions on Geoscience & Remote Sensing
Publication Type :
Academic Journal
Accession number :
124146507
Full Text :
https://doi.org/10.1109/TGRS.2017.2669897