Object Identification Using Multifrequency Emi Data

Unexploded ordnance (UXO) cleanup is the number one priority Army Cleanup Problem<br>requirement and is identified as a major problem throughout the Department of Defense (DOD).<br>A recent SERDP technical report summarizes the status of capability for buried UXO detection,<br>discrimination, and identification as follows: (a) can detect UXO, within definable limits; (b)<br>cannot effectively discriminate UXO anomalies from ‘false alarm’ anomalies; and (c) cannot<br>identify UXO. False alarm anomalies are defined here as geophysical anomalies caused by<br>buried UXO debris, other metallic objects, gravel and cobbles, soil heterogeneities, tree roots,<br>and other natural and cultural features. False alarm anomalies significantly contribute to the cost<br>of UXO remediation due to the large number of unnecessary excavations, A major initiative in<br>the research and development community, therefore, is to develop discrimination (target<br>identification) capabilities. One potential methodology for target identification involves utilizing<br>the broadband scattered electromagnetic induction response. This technique, which is known as<br>Electromagnetic Induction Spectroscopy (EMIS), h as recently become feasible due to the<br>development of the GEM-3 sensor. The GEM-3 is an efficient, broadband, handheld EMI sensor<br>than employs a unique monostatic coil design. Analyzing the EMI spectral content for target<br>identification is not new. In fact, elementary EM theory states that an object must exhibit<br>different responses at different frequencies. All fundamental EM equations involving a timevarying<br>source testify as such. By fully characterizing and identifying an object without<br>excavation, we should be able to significantly reduce the number of false targets. EMIS should<br>be fully applicable to many other problems where target identification and recognition (without<br>intrusive search) are important.