Phase signatures in acoustic-seismic landmine detection

The utility of acoustic-to-seismic coupling systems for landmine detection has been clearly established. In this approach, laser Doppler vibrometers (LDV) are used to measure the different responses to acoustic excitation in ground regions with and without buried landmines. Currently, for most applications, only the magnitude of the surface velocity is investigated and used to construct recognition algorithms. Recently, we introduced phase-based features in the classification scheme, significantly lowering false alarm rates at given detection probabilities. In this paper, we present modeling equations that explain the phase features for ground areas both with and without buried landmines from the perspective of harmonic oscillator models. We also describe the image processing techniques applied to velocity data collected in the time domain with a moving LDV array. The observed signatures are also compared with the prediction of the models described. We also construct classifiers with only magnitude information and both magnitude and phase information for this time-domain data set. Classification results indicate that we can combine magnitude and phase features to improve the detection of buried mines while reducing false alarms. We also find that using phase information improves the distinction between ground regions with buried landmines or man-made clutter objects.