Solving the full nonlinear inverse problem for GPR using a three step method

In order to extract accurate quantitative information out of Ground Penetrating Radar (GPR) measurement data, one needs to solve a nonlinear inverse problem. In this paper we formulate such problem as a nonlinear least squares problem which is non convex. Solving a non-convex optimization problem requires a good initial estimation of the optimal solution. Therefore we use a three step method to solve the above non-convex problem. In a first step the qualitative solution of the linearized problem is estimated to obtain the detection and support of the subsurface scatterers. For this first step Synthetic Aperture Radar (SAR) is proposed. The second step consists out of a qualitative solution of the linearized problem to obtain a first guess for the material parameter values of the detected objects. The method proposed for this is Algebraic Reconstruction Technique (ART), which is an iterative method, starting from the initial value, given by the first step, and improving on this until an optimum is achieved. The final step then consists out of the solution of the nonlinear inverse problem using a variational method.