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Proceedings Paper

Use of standardized source sets for enhanced EMI classification of buried heterogeneous objects
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Paper Abstract

Most unexploded ordinance (UXO) are heterogeneous objects containing parts of different metals, e.g., head, body, tail and fins, copper banding, etc. Recently, low frequency electromagnetic induction (EMI) sensing, based on the EM diffusion phenomena, has shown considerable progress for the detection and discrimination of UXO. EMI responses are sensitive to the type of metal (conductivity and permeability), to the distance between the sensor and scatterer, and to the coupling effects between different parts of the object. Until now, the simple dipole models used to represent EMI response have neglected the coupling and close proximity effects seen for realistic objects. These factors can interact with the particulars of excitation and observation to produce substantially varied signature patterns for a given object. This means that a key requirement in discrimination/inversion processing is to calculate very fast but very realistic EMI responses for actual target types. This work presents a new discrimination technique based on the standardized excitation approximation (SEA). The SEA seeks to identify objects in terms of their characteristic responses to sets of well defined excitations that can be used to describe any primary (excitation) field. In the new SEA system presented here, the standardized excitations are those produced by a standardized source set (SSS), in particular, fictitious magnetic sources distributed mathematically over a surface surrounding a scatterer. Several numerical results are given to illustrate the efficiency and accuracy of the proposed new technique. Finally, the spatial distribution and frequency dependence of responding equivalent sources are analyzed to demonstrate the usefulness of SSS for target discrimination.

Paper Details

Date Published: 21 September 2004
PDF: 12 pages
Proc. SPIE 5415, Detection and Remediation Technologies for Mines and Minelike Targets IX, (21 September 2004); doi: 10.1117/12.541683
Show Author Affiliations
Fridon Shubitidze, Dartmouth College (United States)
Kevin O'Neill, Dartmouth College (United States)
U.S. Army ERDC Cold Regions Research and Engineering Lab. (United States)
Irma Shamatava, Dartmouth College (United States)
Keli Sun, Dartmouth College (United States)
Keith D. Paulsen, Dartmouth College (United States)

Published in SPIE Proceedings Vol. 5415:
Detection and Remediation Technologies for Mines and Minelike Targets IX
Russell S. Harmon; J. Thomas Broach; John H. Holloway, Editor(s)

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