Method for Determining Classification Significant Features from Acoustic Signature of Mine-like Buried Objects

Good feature selection method is an essential step in a classification system. That is especially true for detection systems that have to deal with low signal-to-noise ratio, and varying background conditions, which is the case for landmine detection systems. Proposed method analyzes spectrum of a signal collected from the microphone placed inside the deminers prodder and extracts set of features with best discrimination ability. Feature selection is performed in two stages. First, huge initial set of near 2x10 features is reduced to approximately 100 features and from reduced set best feature subset is selected. Algorithm was successfully applied to the set of unified samples from different materials, as well as on the real landmines and harmless objects.