Continued Discrimination Demonstration Using Advanced EMI Models at Live UXO Sites: Data Quality Assessment and Residual Risk Mitigation in Real Time
Technical Report,30 Apr 2012,31 Mar 2017
White River Technologies, Inc. Newton United States
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This project demonstrated the capability of advanced electromagnetic induction EMI models to perform discrimination of unexploded ordnance UXO at live sites to achieve a high probability of UXO discrimination in situations involving widespread clutter to minimize the number of false positives in such cases to identify all UXO with high confidence to assess the quality of the data and to provide a robust dig threshold that will minimize the risk to regulators. Specific technical objectives were to 1. Use advanced physics-based EMI models to extract robust features that will allow reliable classification when starting from dynamic or cued EMI sensor data. Establish the validity and limitations of these advanced models, taking into account the number of objects in a given cell, their size and material heterogeneity, the geology, and the level of background noise. 2. Combine the advanced models with a statistical model-based approach to select robust classification feature vectors for a specific live UXO site that can reliably and effectively discriminate hazardous targets of interest TOI from nonhazardous items. 3. Deploy advanced EMI and statistical signal processing tools to assess EMI data quality onsite and provide a robust dig-threshold point as a last step, use the different targets extracted extrinsic parameters to mitigate the residual risk due to UXO and to increase the confidence of regulators at the site.
- Ammunition and Explosives
- Electricity and Magnetism
- Magnetic and Electric Field Detection and Detectors