Towards the improvement of automatic identification of underwater acoustic signals using a CHMM-based approach

Abstract

The main problem that originated this paper was how to identify naval targets (ships or submarine) by hearing the underwater sound they produce. This paper reports an approach based on Continuous Hidden Markov Model (CHMM) to identify the naval targets. The Mel frequency cepstral coefficients (MFCCs) were selected to describe the input signal. The general Gaussian density distribution HMM is developed for CHMM system. Several experiments have been conducted to study the effects of speed, distance and the direction of the naval targets on the identification rate (IR) of such targets using our proposed approach. The obtained IR was found to be 100% and kept constant while changing the direction, 91.97% while changing the distance and 58.3% while changing the speed of the target. Results showed that speed has the maximum effect on the identification process.