Adaptive Stochastic Resonance Method For Weak Signal Detection Based On Duffing Oscillator

In the field of precision measurement, signals tend to be coveraged by all kinds of noise, utilizing the characteristic of stochastic resonance to extract the weak signal information from the noise background exactly has been a hot research topic in recent years.In this paper, the two-dimensional Duffing chaotic oscillator is used as the carrier of stochastic resonance; the problem of stochastic resonance induced by various parameters of Duffing chaotic system is studied; the adaptive stochastic resonance weak signal detection based on global artificial fish swarm algorithm and the frequency for weak signal detection method based on Duffing oscillator stochastic resonance and genetic algorithm are proposed respectively, detection model is established, through simulation experiments, verified the detection effect. Specific studies are as follows:the occurrence conditions of stochastic resonance are analyzed from the perspective of Kramers rate; the small-parameter limits of stochastic resonance are deduced according to the adiabatic approximation theory. Based on the stochastic resonance characteristics of Duffing oscillator, Using the method of manual setting parameters to realize the stochastic resonance for weak signals detection under the a stable noise background; Under the background of white Gaussian noise, the influence of bistable system parameters on the structure of stochastic resonance model is studied; Under the background of ? stable noise, the influence of the Duffing oscillator system parameters on the output of the stochastic resonance is studied in detail, It provides theoretical support for the construction of adaptive stochastic resonance system.In order to overcome the shortcomings of the traditional adaptive stochastic resonance and to solve the parameter adjustment problems, an adaptive stochastic resonance method for weak signal detection based on global artificial fish swarm algorithm is proposed, taking nonlinear system parameters as optimization objects, the adaptive stochastic resonance weak signal detection methods based on two-dimensional Duffing system and one-dimensional Langevin systems are compared. Results show: the superiority of the two-dimensional Duffing stochastic resonance system is proved in the condition of same initial signal-to-noise ratio, then,the adaptive stochastic resonance system based on Duffing oscillator is successfully applied to the detection of small target signal under the background of sea clutter, at the same time, the detection performance of small targets in sea clutter background is improved.Aiming at the problem that the weak signal detection methods based on stochastic resonance are restricted by detection range and small-parameter condition,according to the frequency principle of frequency modulation, a frequency modulated method for weak signal detection based on two-dimensional Duffing stochastic resonance and genetic algorithm is presented. Numerical analysis and simulation results show that the proposed method has good generalization ability, the model has good robustness, which can effectively extract weak signal from strong background noise, not only suitable for high or low frequency signal detection, but also suitable for the multifrequency signal detection. This study extends the range of stochastic resonance for weak signal detection, It can provide the basis for the weak signal detection of Duffing chaotic oscillator stochastic resonance in practical engineering.