The objective of this project is to adapt and extend existing strategies for discrimination of unexploded ordnance (UXO) to emerging next generation electromagnetic induction (EMI) sensors and to test discrimination performance at increasingly complex and cluttered sites. Specific technical objectives are to (1) develop robust inversion strategies to extract polarization tensor parameters from both production-type and next generation EMI sensor data that are applicable when the spatial signatures of adjacent anomalies overlap; (2) further develop and test a suite of discrimination strategies (e.g., statistical classification of polarization tensor parameters, library-based matching, statistical classification of data-based features) at increasingly complex and cluttered sites for a wide range of EM sensors (production and next generation); and (3) develop tools and expertise to decide on the optimum discrimination strategy to apply at a newly encountered site.

Through SERDP and ESTCP sponsorship, Sky Research, Inc. and the University of British Columbia-Geophysical Inversion Facility have developed and tested numerous discrimination methodologies using both production-type data (Geonics EM-61 and EM-63, total-field magnetic) and next generation sensor data (e.g., BUD, TEMTADS, MPV, MetalMapper). These signal processing algorithms and strategies will be adapted and extended to support the next series of ESTCP's Classification Pilot Program. The project team anticipates incorporating algorithmic and methodological advances made in SERDP projects MR-1573 (magnetic soils), MR-1629 (robust statistics), and MR-1637 (model selection).

No single discrimination strategy or sensor technology will be universally applicable to the wide variety of UXO-contaminated sites within the United States. Each site typically comprises a different mix of ordnance and clutter and has additional site-specific attributes that influence technology deployment, including cultural infrastructure, vegetation, topography, and geological background. This project aims to provide the Department of Defense (DoD) with flexible, reliable, robust, efficient, and effective signal processing algorithms and strategies that can be adapted to (virtually) any site conditions or EMI sensor technology. The envisioned final outcomes are techniques and algorithms for reliable discrimination of UXO applicable to a wide variety of sites and validated discrimination strategies together with all the resources (software, trained staff, etc.) to immediately apply the technology to other DoD sites. (Anticipated Project Completion - 2013)