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Proceedings Paper

A data-derived time-domain SEA for UXO identification using the MPV sensor
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Paper Abstract

The Man Portable Vector (MPV) sensor is a new mono/multistatic time-domain EMI detector that provides a detailed electromagnetic picture of a target by measuring all three magnetic field components at five distinct receiver positions in over 100 time channels. We have adapted the data-derived Standardized Excitation Approach (SEA) to this sensor. The SEA has been found in the past to make sound predictions in near-field situations, where schemes like the dipole model fail, and in cases where the target under interrogation is heterogeneous and the interactions between its different sections affect the detectable signal. The method replaces a given target with a set of sources placed on a surrounding spheroid and decomposes the sensor primary field into a set of standardized modes. Each of these modes elicits a response from the sources that is intrinsic to the object; it is only the relative weights of the modes that vary with the position and orientation of the target relative to the sensor. The strengths of the sources can be determined by fitting experimental data. Here we review some of the results we obtain when we apply the technique to problems relevant to the identification of unexploded ordnance (UXO). We extract the source parameters using high-quality measurements collected at a UXO test stand and invert unused data sets for location and to discriminate between different objects. We carry out similar experiments with buried objects in order to assess the performance of the method in realistic situations.

Paper Details

Date Published: 29 April 2008
PDF: 12 pages
Proc. SPIE 6953, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XIII, 69531H (29 April 2008); doi: 10.1117/12.777902
Show Author Affiliations
Juan Pablo Fernández, Dartmouth College (United States)
Benjamin Barrowes, U.S. Army Corps of Engineers, ERDC-CRREL (United States)
Kevin O'Neill, Dartmouth College (United States)
U.S. Army Corps of Engineers, ERDC-CRREL (United States)
Irma Shamatava, Dartmouth College (United States)
Fridon Shubitidze, Dartmouth College (United States)
Keli Sun, Dartmouth College (United States)
Schlumberger-Doll Research (United States)


Published in SPIE Proceedings Vol. 6953:
Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XIII
Russell S. Harmon; John H. Holloway; J. Thomas Broach, Editor(s)

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