Underwater UXO classification using matched subspace classifier with synthetic sparse dictionaries
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This work is concerned with the development of a system for the discrimination of military munitions and unexploded ordnances (UXO) from non- UXO's, man-made objects, and other clutter in shallow underwater environments. In this thesis a thorough overview is given of the Matched Subspace Classification (MSC) framework and extensions of this framework when applied to this difficult problem. Acoustic color (AC) features corresponding to calibrated target strength, as a function of frequency and look angle, are generated from the raw sonar returns for munition characterization. Three variations of ...