Adaptive Unsaturated Bistable Stochastic Resonance Multi-Frequency Signals Detection Based on Preprocessing

Abstract

Stochastic resonance (SR) has been widely used for extracting single-frequency weak periodic signals. For multi-frequency weak signals, empirical mode decomposition (EMD) can adaptively decompose the complex signal, but this method also suffers from mode mixing, which affects the accuracy of detection. SR can convert part of the noise energy into signal energy, which compensates for the defects of EMD. According to the advantages of SR and EMD, we constructed a multi-frequency signals detection method using adaptive unsaturated bistable SR based on EMD (EMD-AUBSR). In this study, we avoid the inherent saturation of SR by reconstructing the potential function and improve the multi-frequency signals detection ability by adding the preprocessing element. For strong background noise, the experimental results show that this proposed can effectively detect multi-frequency weak signals and decrease signal aliasing, whereas EMD alone cannot.