Frequency-domain electromagnetic induction sensor data feature extraction and processing for improved landmine detection
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. © 2011 SPIE.
Tantum, SL; Morton, KD; Collins, LM; Torrione, PA
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International Standard Book Number 13 (ISBN-13)
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