Multiple stochastic resonances and inverse stochastic resonances in asymmetric bistable system under the ultra-high frequency excitation

TL;DR

This paper introduces a novel stochastic resonance method using a time-varying parameter in an asymmetric bistable system to enhance detection of ultra-high frequency non-stationary signals, revealing multiple and inverse resonances.

Contribution

It proposes a new stochastic resonance approach with a time-varying parameter to improve weak feature detection in non-stationary signals like UHF-LFM signals.

Findings

Multiple stochastic resonances (MSR) and inverse stochastic resonances (ISR) observed under UHF-LFM excitation.

Resonance regions can deviate or collapse due to system asymmetry.

Optimizing the time scale expands the resonance region, improving response.

Abstract

Ultra-high frequency linear frequency modulation (UHF-LFM) signal, as a kind of typical non-stationary signal, has been widely used in microwave radar and other fields, with advantages such as long transmission distance, strong anti-interference ability, and wide bandwidth. Utilizing optimal dynamics response has unique advantages in weak feature identification under strong background noise. We propose a new stochastic resonance method in an asymmetric bistable system with the time-varying parameter to handle this special non-stationary signal. Interestingly, the nonlinear response exhibits multiple stochastic resonances (MSR) and inverse stochastic resonances (ISR) under UHF-LFM signal excitation, and some resonance regions may deviate or collapse due to the influence of system asymmetry. In addition, we analyze the responses of each resonance region and the mechanism and evolution law of each resonance region in detail. Finally, we significantly expand the resonance region within the parameter range by optimizing the time scale, which verifies the effectiveness of the proposed time-varying scale method. The mechanism and evolution law of MSR and ISR will provide references for researchers in related fields.