Using the adjoint method for solving the nonlinear GPR inverse Problem

Research output: Chapter in Book/Report/Conference proceedingConference paper

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Abstract

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 this into 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 found to obtain the detection and support of the subsurface scatterers. For this first step Synthetic Aperture Radar (SAR) and MUltiple SIgnal Classiffcation (MUSIC) are proposed and compared. 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 ¯nal step then consists out of the solution of the nonlinear inverse problem using a variational method. The paper starts with a discussion of the GPR inverse problem and continues with a short description of the used methods (SAR, MUSIC, ART and adjoint method). Finally an example is given based on simulated data and some conclusions are drawn.
Original languageEnglish
Title of host publicationThe SPIE Conference on Detection and Remediation Technologies for Mines and Minelike Targets XI, paper number 34, Orlando, USA, 2006.
Volume2
Publication statusPublished - 2006

Bibliographical note

Detection and Remediation Technologies for Mines and Minelike Targets XI conference, Orlando, USA.

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