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An analysis of a tikhonov regularized gauss-newton reconstruction approach to GPR tomography

The present work is about the application of a Tikhonov regularized Gauss-Newton scheme to the solution of the nonlinear minimum norm reconstruction problem of GPR tomography, with the aims of (a) setting of a regularization parameter sequence to achieve convergence, (b) evaluation of an iteration matrix at a given nominal parameter estimate, and (c) study the effects of curvatures in parameter and objective-function spaces on the convergence.