Stochastic Resonance Method For Weak Signal Detection Based On Duffing Oscillator

In the field of signal processing,the signal is often accompanied by noise.In order to detect a weak signal in a strong noise environment,the traditional methods regard noise as harmful signal and try to filter them out.The noise is regarded as a favorable signal from another point of view,even if the stochastic resonance method is used to enhance the small target signal.Therefore,the rapid and accurate detection of small target signals in sea clutter environment using stochastic resonance method has become one of the hot research topics in recent years.In this paper,the realization method of stochastic resonance weak signal detection is deeply studied.Using intelligent optimization algorithm to optimize the parameters of Duffing nonlinear system quickly and accurately,and realizing stochastic resonance.Weak periodic signal under strong noise background and small target signal under sea clutter are detected.The specific research contents are as follows:Aiming at the defect that noise can only be adjusted in one direction when noise is adjusted to realize random resonance,and the particle swarm optimization algorithm has the disadvantage of poor searching ability and slow convergence speed.A stochastic resonance weak signal detection method based on adaptive chaotic particle swarm optimization algorithm is proposed in this paper.The adaptive chaotic particle swarm algorithm is used to find the optimal parameters of the system,to realize the stochastic resonance and to detect the weak periodic signal in the strong noise environment.The Duffing system is used to simulate and verify,and the results show that: the stochastic resonance can be realized by this method,which is better than the particle swarm algorithm.The output signal-to-noise ratio is improved by about 2dB,and the weak order-frequency signal can be detected from the strong noise background.In order to compare the effect of stochastic resonance between Duffing system and Langevin system and to detect multi-frequency and large-parameter signals,a stochastic resonance weak signal detection method based on quantum artificial fish swarm algorithm is proposed.The parameters of the two systems are optimized by quantum artificial fish swarm algorithm to realize stochastic resonance.Compared with stochastic resonance,it is found that the stochastic resonance of Duffing oscillator is better,and the output signal-to-noise ratio is increased by about 4dB.It can detect multi-frequency and large parameter signals in strong noise environment.In order to solve the problems of low precision and poor convergence speed of artificial fish swarm optimization algorithm and standard particle swarm optimization algorithm,a stochastic resonance weak signal detection method based on chaotic variable step glowworm swarm algorithm is proposed.The chaotic variable step glowworm swarm algorithm is used to find the optimal parameters of Duffing system accurately and realize stochastic resonance.The proposed method is applied to detect small target signals in sea clutter environment.The simulation results show that this method can achieve stochastic resonance,which is better than the quantum particle swarm optimization algorithm.The output signal-to-noise ratio can be improved by about 5dB.It can detect weak periodic signal in strong noise background and small target signal in sea clutter environment.In this paper,the sea clutter noise signal and small target signal are analyzed and added to the Duffing nonlinear system.Combined with the stochastic resonance theory,the detection method of the stochastic resonance weak signal of the Duffing oscillator is proposed,which is fast and accurate extraction of weak periodic signal in strong noise background and small target signal in sea clutter environment.