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Proceedings Paper

Applying a volume dipole distribution model to next-generation sensor data for multi-object data inversion and discrimination
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Paper Abstract

Discrimination between UXO and harmless objects is particularly difficult in highly contaminated sites where two or more objects are simultaneously present in the field of view of the sensor and produce overlapping signals. The first step in overcoming this problem is estimating the number of targets. In this work an orthonormalized volume magnetic source (ONVMS) approach is introduced for estimating the number of targets, along with their locations and orientations. The technique is based on the discrete dipole approximation, which distributes dipoles inside the computational volume. First, a set of orthogonal functions are constructed using fundamental solutions of the Helmholtz equations (i.e., Green's functions). Then, the scattered magnetic field is approximated as a series of these orthogonal functions. The magnitudes of the expansion coefficients are determined directly from the measurement data without solving an ill-posed inverse-scattering problem. The expansion coefficients are then used to determine the amplitudes of the responding volume magnetic dipoles. The algorithm's superior performance and applicability to live UXO sites are illustrated by applying it to the bi-static TEMTADS multi-target data sets collected by NRL personnel at the Aberdeen Proving Ground UXO teststand site.

Paper Details

Date Published: 29 April 2010
PDF: 11 pages
Proc. SPIE 7664, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XV, 766407 (29 April 2010); doi: 10.1117/12.850651
Show Author Affiliations
Fridon Shubitidze, Dartmouth College (United States)
Sky Research Inc. (United States)
David Karkashadze, Tbilisi State Univ. (Georgia)
Juan Pablo Fernández, Dartmouth College (United States)
Benjamin E. Barrowes, Dartmouth College (United States)
Tbilisi State Univ. (Georgia)
Kevin O'Neill, Dartmouth College (United States)
Tbilisi State Univ. (Georgia)
Tomasz M. Grzegorczyk, Delpsi, LLC (United States)
Irma Shamatava, Dartmouth College (United States)
Sky Research, Inc. (United States)


Published in SPIE Proceedings Vol. 7664:
Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XV
Russell S. Harmon; John H. Holloway; J. Thomas Broach, Editor(s)

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