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Proceedings Paper

Detection of buried mines from array inductive measurements
Author(s): Eric L. Miller; William Clement Karl; Stephen J. Norton
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Paper Abstract

The problem of mine detection and localization from array- based electromagnetic induction data is addressed. An efficient forward scattering model based on the Born approximation is employed. Using insight obtained from this model, a clutter model in the form of a state space system is developed which describes the correlation of the noise both across the sensing array and from one position of the array to the next as the measurement device proceeds down track. A multiple-model detection scheme based on the whitening properties of the Kalman filter is employed to perform the actual mine detection. This approach allows for the detection and localization of buried objects well before the array physically moves over mines. Examples are provided for mines buried directly in front and off to one side of the array.

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: 10.1117/12.324141
Show Author Affiliations
Eric L. Miller, Northeastern Univ. (United States)
William Clement Karl, Boston Univ. (United States)
Stephen J. Norton, Oak Ridge National Lab. (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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