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Proceedings Paper

Analytical solutions for EMI scattering from general spheroids with application in signal inversion for UXO identification
Author(s): Keli Sun; Kevin O'Neill; Lanbo Liu; Fridon Shubitidze; Irma Shamatava; Keith D. Paulsen
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Paper Abstract

EMI (electromagnetic Induction) sensing has been shown to be a very valuable technique for target identification in UXO detection and discrimination. Numerical simulation for EMI sensing of metallic objects is difficult in part because the electromagnetic fields inside the object decay over very small distances, especially at high frequency. This challenges both numerical and analytical techniques. EMI signal inversion has been hampered heretofore by this lack of tractable solutions for basic alternative target shapes. Recently investigators developed an analytical solution formulation for general spheroids. To deal with evaluation problems in those solutions, a high frequency approximation (SPA) was developed, which turns out to have remarkably broadband applicability for steel objects. In this paper we will study its application for UXO identification. One of the most simple and effective procedures for UXO detection and recognition is "fingerprint" matching, for which we know the potential target(s) we are looking for, and we proceed by matching patterns in measured data against those archived for the specific target(s). Since the location and orientation of the target are unknown, we need to estimate them by solving the inverse problem, as a prerequisite for the matching calculations. Both numerical simulation and measurement data indicate that many realistic targets can be approximated by a representative spheroid. The SPA algorithm was then adopted to provide fast forward solution (EMI response from the representative spheroid).. Results show that in a certain range, the spheroid-based forward model can provide sufficiently accurate representation of the responses for a variety of representative target types. Its application in inversion is shown to be very beneficial for target detection and identification.

Paper Details

Date Published: 11 September 2003
PDF: 11 pages
Proc. SPIE 5089, Detection and Remediation Technologies for Mines and Minelike Targets VIII, (11 September 2003); doi: 10.1117/12.487240
Show Author Affiliations
Keli Sun, Dartmouth College (United States)
Kevin O'Neill, U.S. Army Engineer Research & Development Ctr. (United States)
Lanbo Liu, U.S. Army Engineer Research & Development Ctr. (United States)
Fridon Shubitidze, Dartmouth College (United States)
Irma Shamatava, Dartmouth College (United States)
Keith D. Paulsen, Dartmouth College (United States)


Published in SPIE Proceedings Vol. 5089:
Detection and Remediation Technologies for Mines and Minelike Targets VIII
Russell S. Harmon; John H. Holloway; J. T. Broach, Editor(s)

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