|Title||Frequency-domain electromagnetic induction sensor data feature extraction and processing for improved landmine detection|
|Publication Type||Conference Paper|
|Year of Publication||2011|
|Authors||SL Tantum, KD Morton, LM Collins, and PA Torrione|
|Conference Name||Smart Structures and Materials 2005: Active Materials: Behavior and Mechanics|
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.