Weak Radio Signal Detection Based On Cascaded GP-periodic Potential Stochastic Resonance

With the wide application of radio communication technology,the detection of radio has gradually developed into an integral part of the signal processing field.Based on the background of radio detection,this paper conducts research on weak signal detection methods,and proposes the use of a nonlinear algorithm of stochastic resonance to detect radio signal.When a non-linear system is coupled with a periodic excitation signal and noise,the output performance of the system is optimized.The phenomenon of synergy between the non-linear system,the periodic excitation signal and noise is called stochastic resonance.The main work of the paper is to conduct in-depth research on the stochastic resonance system model and combine it with the characteristics of cascaded stochastic resonance to apply it to weak signal detection.Firstly,the theory and method of weak signal detection based on stochastic resonance,as well as several evaluation indicators of stochastic resonance system detection signal are studied in depth.According to the detection requirements of high-frequency radio signal,a detection method that uses damping coefficients and signal-to-noise ratio as evaluation indicator is determined,which can detect high-frequency weak signal more effectively.Secondly,in order to effectively enhance the characteristic frequency of detection,and reduce interference frequency components,and identify target frequency characteristics more clearly,a Gaussian Potential(GP)is combined with a periodic potential system potential well to propose a GP-periodic potential stochastic resonance system model and its application to weak radio signal detection.Through comparative analysis of GP-periodic potential stochastic resonance system,bistable stochastic resonance system,namely traditional stochastic resonance system and periodic potential stochastic resonance system,performes weak radio signal simulation research to analyze the performance of detection signal of different stochastic resonance systems.The stochastic resonance system proposed in this paper not only reduces the interference frequency component information,but also highlights the target characteristic frequency signal.At the same time the stochastic resonance system enhances the spectrum amplitude of the signal to be measured,and improves the utilization of noise by stochastic resonance.Thirdly,based on the study of the GP-periodic potential stochastic resonance system model,in order to detect weak signal with higher intensity noise and further improve the detection effect,two GP-periodic potential stochastic resonance systems are connected in series,and a cascaded GP-periodic potential stochastic resonance system model is proposed.Using the artificial fish swarm algorithm to take the signal-to-noise ratio as the evaluation index,the structural parameters of the cascaded GP-periodic potential stochastic resonance system are optimized,and the system and the GP-periodic potential stochastic resonance system are used to detect weak radio signal in stronger noise.Simulation research verifies that the cascaded GP-periodic potential stochastic resonance optimized based on the artificial fish swarm algorithm can accurately detect the target signal.The spectrum is flatter,and there is less clutter interference,which is an effective method for detecting weak signal.Finally,on the basis of the above research,a Lab VIEW-based weak signal detection system based on stochastic resonance is designed.The experimental verification of the single-frequency signal on the cascaded GP-periodic potential stochastic resonance system and GP-periodic potential stochastic resonance system is based on simulation.Compared with other stochastic resonance systems detection signal,the signal-to-noise ratio is about doubled.It confirms the advantages and feasibility of detecting the weak radio signal of the stochastic resonance system established in this paper and further validates the validity of the stochastic resonance model proposed in this paper.