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Proceedings Paper

Advanced UXO discrimination: resolving multiple targets and overlapping EMI signals
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Paper Abstract

In this paper we employ advanced electromagnetic induction models to resolve multiple targets with overlapping EMI signals-i.e. to discriminate objects of interest, such as unexploded ordnance (UXO), from innocuous items. The models include a) a joint diagonalization (JD) technique that takes data from next-generation EMI sensors and uses the eigenvalues of the multistatic response matrix to estimate the number of potential targets, and b) the orthonormalized volume magnetic source (ONVMS) model, a physically complete, fast, and accurate forward model whose representation of a target's intrinsic EMI response is used to extract classification parameters. In the given approach the overall EMI inversion and classification problem proceeds as follows: first, the JD is applied to the data and the number of targets is estimated; once this is known, the ONVMS is combined with an optimization technique to yield the location and orientation of each buried object, as well as the amplitude of its ONVMS. Finally, a total ONVMS is calculated for each object and used as a discriminant to distinguish between UXO and non-UXO items and between different kinds of UXO. We illustrate the applicability of our multi-target analysis technique by using it on several teststand and live-site datasets collected with the TEMTADS sensor array. We end by demonstrating the superior performance of the ONVMS by applying it to multi-target blind-test data compiled at the Aberdeen Proving Ground test-stand facility.

Paper Details

Date Published: 31 May 2011
PDF: 12 pages
Proc. SPIE 8017, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XVI, 80170A (31 May 2011); doi: 10.1117/12.884405
Show Author Affiliations
Fridon Shubitidze, Thayer School of Engineering at Dartmouth (United States)
Sky Research Inc. (United States)
Benjamin E. Barrowes, Sky Research Inc. (United States)
U.S. Army Cold Regions Research and Engineering Lab. (United States)
Irma Shamatava, Sky Research Inc. (United States)
Thayer School of Engineering at Dartmouth (United States)
Juan Pablo Fernandez, Consultant (United States)
Alex Bijamov, Thayer School of Engineering at Dartmouth (United States)
Kevin O'Neill, Sky Research Inc. (United States)
U.S. Army Cold Regions Research and Engineering Lab. (United States)


Published in SPIE Proceedings Vol. 8017:
Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XVI
Russell S. Harmon; John H. Holloway; J. Thomas Broach, Editor(s)

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