Final Report: Resolving and Discriminating Overlapping Anomalies from Multiple Objects in Cluttered Environments
Abstract
The primary objective of the project 55000-EV entitled Resolving and Discriminating Overlapping Anomalies from Multiple Objects in Cluttered Environments was to mitigate the effects of dispersed metallic clutter, to resolve the contribution of independent or coupled objects to the composite EMI data, and to discriminate each object of interest based on its response under more realistic field conditions. Specific objectives were: 1. Research techniques that minimize the contribution of clutter by using upward projection methods on data acquired at field sites with instruments such as the MPV, TEMTADS, BUD, and GEM-3D 2. Develop an N-target locator that, without any computationally expensive optimizations, provides an estimate of the number of objects within in a sensors field of view and their locations and orientations. 3. Formulate robust classifiers that segregate N objects into UXO and non-UXO based on their isolated EMI responses. 4. Discriminate UXO-like targets using rigorous models (NSMS, SEA) which explicitly include coupling between targets if required.To address these objectives, under this project first we developed physically complete forward approaches:? Standardized Excitation Approach for understanding modeling targets EMI responses in great details.? Normalized surface magnetic source model (NSMS) for EMI sensors data inversion and classification.? Orthonormalized volume magnetic source model (ONVMS) for next generation EMI systems data analysis and subsurface multiple targets classification.
Document Details
- Document Type
- Technical Report
- Publication Date
- Dec 15, 2015
- Accession Number
- AD1053272
Entities
People
- Alex Bijamov
- D Karkashadze
- Fridon Shubitidze
- Irma Shamatava
- John B. Sigman
- Juan Pablo Fernandez
- Yinlin Wang
Organizations
- Dartmouth College