Bark-wavelet Analysis and Hilbert–Huang Transform for Underwater Target Recognition

Recognizing the underwater targets by the radiated noise information is one of the most significant subjects in the area of underwater acoustics. A novel recognition approach which consists of the algorithms of Bark-wavelet analysis, Hilbert–Huang transform and support vector machine is proposed based on the theory of auditory perception. The performance of the proposed method is validated by comparing with traditional method and evaluated by the recognition experiments for SNRs of 0 dB, 5 dB, 10 dB, 15 dB and 20 dB. The results show that the average recognition rate of the method is above 88% and can be increased by 0.75%–6.25% under various SNR conditions compared to the baseline system.