Feature-based Detection and Discrimination at DuPont's Lake Success Business Park, Connecticut
Abstract
The objective of this demonstration was to determine if laser-positioned, high-density EM61 data acquired in a moving survey mode could support feature-based discrimination decisions for a canopied site in Bridgeport Connecticut. Inversion results were benchmarked using cued data acquired in a controlled, gridded approach over 40 targets. The site was seeded with inert UXO, ranging in size from 37mm to 105mm projectiles. We inverted the measured EM61 field data assuming a point dipole source and performed classification using a support vector machine classifier. We compared parameter estimates derived from both data sets and evaluated overall discrimination performances. Results indicated that the laser-positioned EM61 data were not of sufficient quality to discriminate UXO from non-UXO. Of the 58 seeded items that were surveyed, 41 were ranked as high confidence ordnance, 10 were ranked as high confidence clutter, and 7 remained unclassified.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jan 01, 2007
- Accession Number
- ADA478316
Entities
People
- Dean A. Keiswetter
Organizations
- Leidos