HMM-based underwater target classification with synthesized active sonar signals

This paper deals with underwater target classification using synthesized active sonar signals. Firstly, we synthesized active sonar returns from 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. Experimental results depending on the number of observations and signal-to-noise ratio are presented with our discussions.