Comparison of different classification algorithms for underwater target discrimination

Authors:
Donghui Li;M. R. Azimi-Sadjadi;M. Robinson
Affiliations:
Dept. of Electr. & Comput. Eng., Colorado State Univ., Fort Collins, CO, USA;-;-
Venue:
IEEE Transactions on Neural Networks
Year:
2004

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Abstract

Classification of underwater targets from the acoustic backscattered signals is considered. Several different classification algorithms are tested and benchmarked not only for their performance but also to gain insight to the properties of the feature space. Results on a wideband 80-kHz acoustic backscattered data set collected for six different objects are presented in terms of the receiver operating characteristic (ROC) and robustness of the classifiers wrt reverberation.