A New Ship-Radiated Noise Feature Extraction Technique Based on Variational Mode Decomposition and Fluctuation-Based Dispersion Entropy

Abstract

Sea environment complexity and underwater acoustic channels make it hard to extract features of ship-radiated noise signals. This paper presents a novel feature extraction method using the advantages of variational mode decomposition (VMD), fluctuation-based dispersion entropy (FDE) and self-organizing feature map (SOM). Firstly, VMD decomposition of the original signal is used to get a group of bandwidth-limited intrinsic mode functions (IMFs). Then, the difference between the FDE of each IMF and the original signal is calculated, respectively; the IMF with the smallest difference (SIMF) is selected to calculate the FDE as the feature vector. Finally, the characteristic vectors are sent to the SOM classifier to categorize the original signal. The proposed method is applied to feature extraction of real ship-radiated noise signals. The results show that this method is more precise for ship-radiated noise signals feature extraction.