Preliminary Investigation of the NCP Parameter-Choice Method for Inverse Scattering Problems Using BIM: 2-D TM Case

Abstract

A new method of choosing the regularization parameter, originally developed for a general class of discrete ill-posed problems, is investigated for electromagnetic inverse scattering problems that are formulated using a penalty method. This so-called normalized cumulative periodogram (NCP) parameterchoice method uses more information available in the residual vector, as opposed to just its norm, and attempts to choose the largest regularization parameter that makes the residual resemble white noise. This is done by calculating the NCP of the residual for each choice of the regularization parameter, starting from large values and stopping at the first parameter which puts the NCP inside the Kolmogorov-Smirnov limits. The main advantage of this method, as compared, for example, to the L-curve and Generalized Cross-Validation (GCV) techniques, is that it is computationally inexpensive and therefore makes it an appropriate technique for large-scale problems arising in inverse imaging. In this paper, we apply this technique to the general-form Tikhonovregularized functional arising in the 2-D/TM inverse electromagnetic problem, which is formulated via an integral equation and solved using the Born Iterative Method (BIM).