Abstract
Underwater target recognition and classification has been a field of considerable importance due to its multidimensional applications. Much attention has been focused on this area and various underwater signal processing schemes have been devised over the time. Hidden Markov Models, because of their robustness, provide an effective architecture for the classification of underwater noise sources. A methodology is presented, in this paper, for the design and performance analysis of an HMM based underwater signal classification system, utilizing the Discrete Sine Transform based target specific features. Simulation results have been presented for typical underwater noise waveforms, such as Boat and Dolphin noises.
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