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The paper deals with the problem of vessel identification. The presented method is based on fractional Brownian analysis of vessel power spectrum. The measurements for three vessels were carried out with the use of a mobile measuring module in the Gulf of Gdansk; next, the information obtained from sound spectra was identified. Two classifiers connected with fractional Brownian motion were used: the first-order increments and the standard deviation. Finally, classification decision was made using the Mahalanobis distance. Numerical experiments were performed using MATLAB.

An Application of Fractional Brownian Motion to Vessel Identification Based on its Sound Spectrum