Research On Weak Signal Detection And Extraction Method Based On Stochastic Resonance

In the case of bad communication environment,there is strong noise in the channel,and the signal is fading,the signal is completely annihilated by noise at the receiving end,and the communication quality is seriously affected.In the environment of low signal-to-noise ratio,how to detect weak signal and extract its waveform has become a research hotspot in the field of wireless communication.Most methods achieve the purpose of weak signal detection and extraction by suppressing noise.However,at the same time,the energy of the wanted signal is inevitably lost in the linear system,which leads to the limited improvement of signal-to-noise ratio.Stochastic resonance,as a nonlinear dynamic theory,can use the energy of noise to enhance weak signals,and the output signal-to-noise ratio is greatly improved.In this paper,stochastic resonance is applied to weak communication signal detection and extraction.The main research contents and achievements are as follows:Firstly,aiming at the problem that the stochastic resonance phenomenon cannot be generated in the large-parameter signal,a new pre-processing method for large-parameter signal is proposed.The amplitude is linearly compressed by the amplitude compression factor,and the relative relationship between the signal frequency and the calculation step is changed by the scale transformation factor.The signal amplitude,noise intensity and signal frequency are controlled within the small parameter conditions of the adiabatic approximation theory respectively,so that the stochastic resonance can adapt to any signal.Secondly,in view of the poor detection performance of traditional signal detection methods in the case of low signal-tonoise ratio,a weak signal detection method based on stochastic resonance is proposed.Artificial fish swarm algorithm is introduced to optimize the parameters of stochastic resonance,and the iterative process is improved to shorten the iteration period,improve the convergence speed,and improve the detection performance in low signal-to-noise ratio.Finally,aiming at the difficult problem of signal extraction under low signal-to-noise ratio,a weak signal extraction method based on stochastic resonance distortion recovery was proposed.The artificial fish swarm algorithm was introduced to optimize the parameters of the recovery module to avoid the problem of inaccurate recovery caused by fixed parameters,improve the extraction performance and reduce the bit error rate.The method of weak signal detection and extraction based on stochastic resonance can well adapt to the environment of low signal-to-noise ratio.At the same time,through the optimization of intelligent optimization algorithm,the detection performance and extraction performance have been greatly improved.In this paper,stochastic resonance theory is applied to communication signal processing,which broadens the application range of stochastic resonance and provides a new idea for weak signal processing.