Adaptive feature enhancement of modulation spectrum of ship radiation noise

The Detection of Envelope Modulation on Noise (DEMON) has been widely used in passive sonar target identification for determining the operational status and propeller structure characteristics of ships. However, the traditional DEMON spectrum is susceptible to environmental noise, which increases the difficulty of feature extraction. To address this issue, this paper investigates an adaptive feature enhancement method that combines Variational Mode Decomposition (VMD) and Singular Value Decomposition (SVD). The VMD algorithm utilizes variational equations to achieve adaptive modal decomposition of multiple feature components, while SVD utilizes the uncorrelated nature of signal and noise to achieve background noise reduction. Simulation results demonstrate that the feature strength and output signal-to-noise ratio of the VMD-SVD algorithm are higher than those of the traditional DEMON algorithm under both uniform and non -uniform modulation modes. Furthermore, processing of actual data validates the superiority of the VMD-SVD algorithm over the traditional DEMON algorithm, with the feature strength and output signal-to-noise ratio being maximally increased by 3 dB and 3.8 dB, respectively, compared to the traditional algorithm.