Imaging subsurface contaminants using inverse scattering techniques

Use of ground-penetrating radar in high-resolution imaging of subsurface targets has been investigated extensively in recent years. Imaging of subsurface contaminants is one of the applications that has attracted more attention in recent years with the increasing awareness about the environment. In this paper, a technique for imaging of subsurface contaminants is presented. The imaging problem is formulated as an electromagnetic inverse scattering problem. A nonlinear .technique used for solving the problem is outlined. This technique is based on solving the imaging problem iteratively. A forward and an inverse scattering problem is solved at each step of this technique. The forward problem is solved using the finite-difference time-domain (FDTD) technique whereas the inverse problem is formulated as a constrained optimization problem. The solution to the inverse problem is obtained by using the method of regularization. One of the problems associated with applying this technique for subsurface imaging applications is the evaluations of the integral of the Green's function for an inhomogeneous dielectric half-space. The FDTD technique is used to evaluate the Green's function which is then integrated numerically. Several simulations are performed with typical background and object properties. A ground-air dielectric half-space is considered for all simulations. For subsurface contaminant imaging, this techinque provides good-quality images for typical objects and ground properties with just a single iteration. This technique results in good reconstructions even with an inhomogeneous ground. The use of FDTD for solving the forward scattering problem provides the capability to model complex object geometries.