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Proceedings Paper

Identification of metallic mines using low-frequency magnetic fields
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Paper Abstract

This paper addresses the issue of identifying conduction objects based on their response to low frequency magnetic fields -- an area of research referred to by some as magnetic singularity identification (MSI). Real time identification was carried out on several simple geometries. The low frequency transfer function of these objects was measured for both cardinal and arbitrary orientations of the magnetic field with respect to the planes of symmetry of the objects (i.e., different polarizations). Distinct negative real axis poles (singularities) associated with each object form the basis for our real-time identification algorithm. Recognizing this identification problem as one of inference form incomplete information, application of Bayes theorem leads to a generalized likelihood ratio test (GLRT) as a solution to the M-ary hypothesis testing problem of interest here. Best performance, measured through Monte Carlo simulation presented in terms of percent correct identification versus signal-to- noise ratio, was obtained with a single pole per object orientation.

Paper Details

Date Published: 4 September 1998
PDF: 12 pages
Proc. SPIE 3392, Detection and Remediation Technologies for Mines and Minelike Targets III, (4 September 1998); doi: 10.1117/12.324233
Show Author Affiliations
Lloyd S. Riggs, Auburn Univ. (United States)
Jonathan Martin Mooney, Auburn Univ. (United States)
Daniel E. Lawrence, Auburn Univ. (United States)
J. Thomas Broach, U.S. Army Night Vision & Electronic Sensors Directorate (United States)
Anh H. Trang, U.S. Army Night Vision & Electronic Sensors Directorate (United States)


Published in SPIE Proceedings Vol. 3392:
Detection and Remediation Technologies for Mines and Minelike Targets III
Abinash C. Dubey; James F. Harvey; J. Thomas Broach, Editor(s)

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