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Abstract
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The acoustic signals radiated from the marine vessels contain information about their machinery characteristics that can be useful
for the detection and classification purposes. To achieve reliable accuracy in classification task, informative discriminant features
should be extracted from received signals. STFT (Short Time Fourier Transform) is the most basic and popular signal processing
method in the classification process of passive sonar signals, but it suffers from some fatal shortages. In this work, we present an
improved spectrogram based on the windowed fractional-Fourier transform of the acoustic signal with the optimal FrFT order,
which accounts for signals with multiple non-stationary components. The discriminating capability of two groups of features
extracted from the processed signal, using PCA and LDA techniques, have been compared. The achieved results declare the
significant improvement in the classification accuracy by the new proposed method using the LDA feature extraction technique
and the proper order of FrFT. However, in order to eliminate the constraints of searching for the proper FrFT-order and increasing
the reliability and stability of practical sonar classification systems, a parallel combination of the proposed method is introduced.
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