Abstract
Abstract Ground penetrating radar (GPR) has a wide range of applications in soil detection. In this article, we model the three-dimensional (3-D) random medium in GPR based on soil fractal characteristics. We use a 3-D Fractal Brownian Motion (FBM) spectral density function to simulate non-uniform media and discuss the effects of Hurst exponent and scale coefficients on the modeling results. The Hurst exponent is an important indicator in FBM, which reflects the degree of disturbance in the medium. Soil water content (SWC) is a key factor affecting the heterogeneity of soil media, and the distribution of soil dielectric properties also depends on SWC. Therefore, we use SWC data to obtain the Hurst exponent through Rescaled-range (R/S) analysis. Finally, a 3-D random medium model is established based on actual SWC data, and GPR forward simulation is performed on the established model by the finite difference time domain (FDTD) method. The simulation results show that the random medium modeling method based on soil fractal characteristics can provide an effective modeling tool for GPR soil detection.
Published Version
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