Fast direct and inverse EMI algorithms for enhanced identification of buried UXO with real EMI data

Discrimination of buried unexploded ordinance (UXO) from innocuous buried items remains a challenging, top priority problem for the electromagnetic induction (EMI) sensing community. In general, classification is an inverse problem, requiring very fast and accurate representation of the target response. To address this critical issue, this paper presents a very fast, rigorous way to compute EMI scattering from a realistically complex, composite target. Full interaction between all parts of the object are included in the calculations. The method is based on a hybrid of the full method of auxiliary source (MAS) and the MAS-thin skin depth approximation formulation (MAS-TSA), together with new modal decomposition and reduced source set techniques. For general excitation, a primary field is decomposed into the fundamental spheroidal modes on a fictitious spheroid surrounding a real target. Finally the total response from the target is reproduced using only a few auxiliary magnetic charges. A least square minimization is used for discrimination an unseen object's orientation and position. Numerical results are given and compared with experimental data.