Automatic classification of underwater sonar signals

Much work has been performed recently in the area of automatic recognition of the sonar signals to reduce the operator load when confronted with many beams of data concurrently. In this paper we applied and compared different feature extraction methods such as the wavelet basis method, discrete cosine transform method (DCT) and linear prediction method (LP) and then we applied neural network techniques to the processing of sonar signal classification.