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Modeling of Multilayered Media Green’s Functions With Rough Interfaces.

Authors :
Jonard, Francois
Andre, Frederic
Pinel, Nicolas
Warren, Craig
Vereecken, Harry
Lambot, Sebastien
Source :
IEEE Transactions on Geoscience & Remote Sensing. Oct2019, Vol. 57 Issue 10, p7671-7681. 11p.
Publication Year :
2019

Abstract

Horizontally stratified media are commonly used to represent naturally occurring and man-made structures, such as soils, roads, and pavements, when probed by ground-penetrating radar (GPR). Electromagnetic (EM) wave scattering from such multilayered media is dependent on the roughness of the interfaces. In this paper, we developed a closed-form asymptotic EM model considering random rough layers based on the scalar Kirchhoff-tangent plane approximation (SKA) model that we combined with planar multilayered media Green’s functions. In order to validate our extended SKA model, we conducted simulations using a numerical EM solver based on the finite-difference time-domain (FDTD) method. We modeled a medium with three layers—a base layer of perfect electric conductor (PEC) overlaid by two layers of different materials with rough interfaces. The reflections at the first and at the second interface were both well reproduced by the SKA model for each roughness condition. For the reflection at the PEC surface, the extended SKA model slightly overestimated the reflection, and this overestimation increased with the roughness amplitude. Good agreement was also obtained between the FDTD simulation input values and the inverted root mean square (rms) height estimates of the top interface, while the inverted rms heights of the second interface were slightly overestimated. The accuracy and the performances of our asymptotic forward model demonstrate the promising perspectives for simulating rough multilayered media and, hence, for the full waveform inversion of GPR data to noninvasively characterize soils and materials. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
01962892
Volume :
57
Issue :
10
Database :
Academic Search Index
Journal :
IEEE Transactions on Geoscience & Remote Sensing
Publication Type :
Academic Journal
Accession number :
139437314
Full Text :
https://doi.org/10.1109/TGRS.2019.2915676