A novel feature extraction method for ship-radiated noise

To improve the feature extraction of ship-radiated noise in a complex ocean environment, a novel feature extraction method for ship-radiated noise based on complete ensemble empirical mode decomposition with adaptive selective noise (CEEMDASN) and refined composite multiscale fluctuation-based dispersion entropy (RCMFDE) is proposed. CEEMDASN is proposed in this paper which takes into account the high frequency intermittent components when decomposing the signal. In addition, RCMFDE is also proposed in this paper which refines the preprocessing process of the original signal based on composite multi-scale theory. Firstly, the original signal is decomposed into several intrinsic mode functions (IMFs) by CEEMDASN. Energy distribution ratio (EDR) and average energy distribution ratio (AEDR) of all IMF components are calculated. Then, the IMF with the minimum difference between EDR and AEDR (MEDR) is selected as characteristic IMF. The RCMFDE of characteristic IMF is estimated as the feature vectors of ship-radiated noise. Finally, these feature vectors are sent to self-organizing map (SOM) for classifying and identifying. The proposed method is applied to the feature extraction of ship-radiated noise. The result shows its effectiveness and universality.