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Proceedings Paper

Frequency domain electromagnetic induction sensor data feature extraction and processing for improved landmine detection
Author(s): Stacy L. Tantum; Kenneth D. Morton; Leslie M. Collins; Peter A. Torrione
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Paper Abstract

Frequency-domain electromagnetic induction (EMI) sensors have the ability to provide target signatures which enable discrimination of landmines from harmless clutter. In particular, frequency-domain EMI sensors are well-suited for target characterization by inverting a physics-based signal model. In many model-based signal processing paradigms, the target signatures can be decomposed into a weighted sum of parameterized basis functions, where the basis functions are intrinsic to the target under consideration and the associated weights are a function of the target sensor orientation. The basis function parameters can then be used as features for classification of the target as landmine or clutter. In this work, frequency-domain EMI sensor data feature extraction and processing is investigated, with a variety of physics-based models and statistical classifiers considered. Results for data measured with a prototype frequency-domain EMI sensor at a standardized test site are presented. Preliminary results indicate that extracting physics-based features followed by statistical classification provides an effective approach for classifying targets as landmine or clutter.

Paper Details

Date Published: 23 May 2011
PDF: 12 pages
Proc. SPIE 8017, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XVI, 80170B (23 May 2011); doi: 10.1117/12.884769
Show Author Affiliations
Stacy L. Tantum, Duke Univ. (United States)
Kenneth D. Morton, Duke Univ. (United States)
Leslie M. Collins, Duke Univ. (United States)
Peter A. Torrione, Duke Univ. (United States)


Published in SPIE Proceedings Vol. 8017:
Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XVI
Russell S. Harmon; John H. Holloway; J. Thomas Broach, Editor(s)

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