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Journal of Sensors
Volume 2018 (2018), Article ID 6593037, 14 pages
Research Article

A GTCC-Based Underwater HMM Target Classifier with Fading Channel Compensation

1Research & Development Centre, Bharathiar University, Coimbatore 641046, India
2Department of Electronics, Cochin University of Science and Technology, Cochin 682022, India

Correspondence should be addressed to Shameer K. Mohammed; moc.liamg@ilaredyh.reemahs

Received 19 August 2017; Revised 16 November 2017; Accepted 14 January 2018; Published 3 April 2018

Academic Editor: Juan C. Cano

Copyright © 2018 Shameer K. Mohammed et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Underwater acoustic target classifiers are found to have many applications in military and security areas where a higher degree of prediction accuracy is needed that makes classifier efficiency and reliability an interesting subject. Classifiers are often trained with known acoustic target specimens with their characteristic feature set and tested with measurements obtained from the sonar that is deployed in the surveillance or observation zone. The selection of source-specific deterministic features in automatic target recognition (ATR) system is very significant, since it determines the reliability, efficiency, and success rate of the classifier. The robustness of the gammatone cepstral coefficients (GTCC) in combination with the statistical Euclidean distance, artificial neural network (ANN), and hidden Markov model (HMM) classifiers has been investigated, and its performance is compared with that of other feature extraction schemes. The classifier performance has been analyzed in Rayleigh fading conditions, based on which the performance is enhanced by incorporating an autoregressive (AR) Rayleigh fading channel compensation. The performance of the classifier in different operating conditions is investigated, with underwater target signals consisting of the real field data collected during expedition, and the results are presented in this paper.