Parameter matched stochastic resonance with damping for passive sonar detection

Stochastic resonance (SR) has been proven effective for weak signal detection under low signal-to-noise ratio (SNR) conditions. In this paper, a parameter matched stochastic resonance (PMSR) method is proposed to enhance the detection and extraction ability to weak signatures of moving vessels. Theoretical matched framework is established with a damped bistable SR model by optimizing the input-output signal-to-noise ratio improvement (SNRI) to nonlinear system parameters. By selecting a proper damping factor within a determinate constraint range, a weak periodic signal, background noise, and nonlinear system can be matched in generating a desired optimal output in the regime of matched parameter relationship. Then, we propose a PMSR based energy detection (ED) algorithm by taking the fully advantage of the Lorentzian characteristics. Numerical simulation analyses and application verifications are carried out to validate the effectiveness and efficiency of the proposed method, which reflects an excellent enhancement performance especially for low-frequency ship signatures.