Sensing of unexploded ordnance with magnetometer and induction data: theory and signal processing

We consider the detection of subsurface unexploded ordnance via magnetometer and electromagnetic-induction (EMI) sensors. Detection performance is presented, using model-based signal processing algorithms. We first develop and validate the parametric models, using both numerical and measured data. These models are then applied in the context of feature extraction, and the features are processed via two signal-processing algorithms. The detection algorithms are discussed in detail, with comparisons made based on performance with measured magnetometer and EMI data.

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