A novel method for frequency feature extraction of ship radiated noise based on variational mode decomposition, double coupled Duffing chaotic oscillator and multivariate multiscale dispersion entropy

Abstract

The processing of ship radiated noise is a research hotspot in the field of military and marine resource exploration. Frequency characteristic is an important characteristic of ship radiated noise. Ship radiated noise consists of line spectrum and continuous spectrum, and the frequency features are mainly reflected by line spectrum. Accurate extraction of line spectrum frequency feature is of great significance to realize ship target classification and recognition. This paper proposes a novel method for frequency feature extraction of ship radiated noise based on variational mode decomposition (VMD), double coupled Duffing chaotic oscillator (DCDCO) and multivariate multiscale dispersion entropy (mvMDE), named VMD-DCDCO-mvMDE. For the first time, DCDCO and mvMDE are applied to the feature extraction of ship radiated noise. Firstly, ship radiated noise is decomposed into a series of intrinsic mode functions (IMFs) by VMD. The decomposition layers K of VMD are determined according to the decomposition results of EMD. Secondly, adjust γand let d = 2 to leave DCDCO in critical chaotic state and detect the frequency of low frequency IMF. The mvMDE of the output signal of chaotic oscillator is calculated in the frequency range of DCDCO in the large scale periodic state, and the accurate frequency is determined by the minimum value of mvMDE. Finally, the extracted frequency feature parameters are input into the self-organizing mapping (SOM) neural network to classify and recognize different ship targets. In the analog signal experiment, the maximum frequency error of VMD-DCDCO-MVMDE extraction is only 0.01%, while the minimum error of the current method is 0.33%. The proposed method can extract frequency feature more accurately. In the measured signal experiment, the results show that the correct rate of the proposed method can reach 100% for the classification and recognition of the three groups of ship radiated noise, while the correct rate of the current method is the highest at 84%. The proposed method can effectively extract the line spectrum frequency feature of ship radiated noise, and the classification accuracy is higher, and the recognition effect is better.