Regularization Approaches for a Non-Iterative Eigenfunction-Based Electromagnetic Inversion Algorithm

Several options for regularizing a novel non-iterative eigenfunction-based inverse-source solver related to 2D Electromagnetic Imaging are presented. Regularization is implemented in the form of constraint equations that use the fact that all contrast sources outside the imaging domain are zero. The different options are evaluated via their improved imaging performance on a few examples based on synthetically derived forward data. It will be shown that the proper selection of constraint equations can significantly enhance the performance of this non-iterative algorithm.