HMM-Based Underwater Target Classification with Synthesized Active Sonar Signals

Taehwan KIM  Keunsung BAE  

IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences   Vol.E94-A   No.10   pp.2039-2042
Publication Date: 2011/10/01
Online ISSN: 1745-1337
DOI: 10.1587/transfun.E94.A.2039
Print ISSN: 0916-8508
Type of Manuscript: LETTER
Category: Digital Signal Processing
pattern recognition,  sonar signal processing,  hidden Markov models,  

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This paper deals with underwater target classification using synthesized active sonar signals. Firstly, we synthesized active sonar returns from a 3D highlight model of underwater targets using the ray tracing algorithm. Then, we applied a multiaspect target classification scheme based on a hidden Markov model to classify them. For feature extraction from the synthesized sonar signals, a matching pursuit algorithm was used. The experimental results depending on the number of observations and signal-to-noise ratios are presented with our discussions.