Classification of ships using autocorrelation technique for feature extraction of the underwater acoustic noise

The paper applies spectral analysis to the underwater acoustic noise radiated by ships. A frequency band is specified to characterize the sound produced by different platforms. Hence the paper proposes a new technique for feature extraction by applying autocorrelation technique and discrete cosine transform. The features extracted are employed by a recognition engine that uses Gaussian mixture model for the classification of the underwater acoustic noise radiated by ships. The performance of the recognition is investigated for various settings of the proposed technique.