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Near field ( ~ 1 m) electromagnetic induction (EMI) sensing, from 10's of Hz up to 100's of kHz, has been successful in detecting subsurface metallic targets. However, the discrimination of buried unexploded ordinance (UXO) from innocuous objects still remains a challenging problem. The EM fields radiated by both antenna and target fall off very sharply as function ~1/R 3 , for a combined decay rate of ~ 1/R 6 . Therefore EMI sensors affect different materials and sections of the target differently [1-2], and signals depend very strongly on what parts of the target are closest to the sensor. Taking into account proximity effects is particularly important for identification and discrimination of actual UXO. The classification of unseen, buried objects, which in general is an inverse problem, requires very fast and accurate representation of the target response. To address these critical issues and to enhance of UXO identification, this paper presents very fast, rigorous ways to compute EMI scattering from a composite target. The method is based on the hybrid full method of auxiliary source (MAS) [1] and MAS-thin skin depth approximation technique (MAS-TSA) [3], together with modal decomposition and reduced source set techniques. For general excitation, a primary field is decomposed into the fundamental spheroidal modes on a fictious spheroid surrounding a real target. Then the problem is solved for each spheroidal mode, taking advantage of axial symmetry. Finally the total response from the target is reproduced using only a few auxiliary magnetic charges. The numerical results are given and compared with experimental data.

Efforts to discriminate buried unexploded ordnance from harmless surrounding clutter are often hampered by the uncertainty in the number of buried targets that produce a given detected signal. We present a technique that helps determine that number with no need for data inversion. The procedure is based on the joint diagonalization of a set of multistatic response (MSR) matrices measured at different time gates by a time-domain electromagnetic induction sensor. In particular, we consider the Naval Research Laboratory's Time-Domain Electromagnetic Multisensor Towed Array Detection System (TEMTADS), which consists of a 5 × 5 square grid of concentric transmitter/receiver pairs. The diagonalization process itself generalizes one of the standard procedures for extracting the eigenvalues of a single matrix; in terms of execution time, it is comparable to diagonalizing the matrices one by one. We present the method, discuss and illustrate its mathematical basis and physical meaning, and apply it to several actual measurements carried out with TEMTADS at a test stand and in the field at the former Camp Butner in North Carolina. We find that each target in a measurement is associated with a set of nonzero timedependent MSR eigenvalues (usually three), which enables estimation of the number of targets interrogated. These eigenvalues have a characteristic shape as a function of time that does not change with the location and orientation of the target relative to the sensor. We justify analytically and empirically that symmetric targets have pairs of eigenvalues with constant ratios between them.