Abstract
ABSTRACTGround‐penetrating radar (GPR) modelling is employed to study the electromagnetic wave scattering that emanates from a rough subsurface interface. The numerical analysis is achieved by using a finite‐difference time‐domain numerical modelling algorithm. For the 2D GPR models, the rough interfaces are generated using both Gaussian and fractal statistics. For a given root mean square interface roughness height, we study the effect that the change in correlation length has on the incident wavefield for a randomly generated surface with a Gaussian roughness spectrum. Similarly, for an interface generated using fractal statistics, we examine the effect of fractal dimension for two different values of maximum wavenumber. For the Gaussian case, the correlation length is the most important parameter in defining the target signature. But, when fractals are used, an increase in clutter is observed as the fractal dimension increases. In addition, the clutter is more pronounced when the highest value of maximum wavenumber is used. Detection performance is evaluated by utilising 3D ground‐penetrating radar models. Comparing the 3D models with and without the presence of a rough subsurface interface, increased wavefield attenuation and strong depolarization effects were observed from a fractal subsurface terrain.
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