Detection Algorithm Of BPSK Signal Based On Tri-stable Stochastic Resonance

In the traditional view,the method of improving the detection of binary phase shift keying(BPSK)signals is mainly to improve the signal characteristics or reduce the noise characteristics,but when the noise is suppressed,it will weaken the signal to be tested,and Stochastic resonance detection algorithm makes up for this deficiency.In order to improve the information transmission performance,this paper mainly focuses on the detection method of tri-stable Stochastic resonance of BPSK signal,and the main contents are as follows:Firstly,build the model of the BPSK signal tri-stable Stochastic resonance system,derive the expressions of the output signal-to-noise ratio and the signal-to-noise ratio gain of the system.At the same time,take the signal-to-noise ratio gain as the measurement index,explore the impact of system parameters and noise intensity on the resonant output.In addition,the simulation results in the strong noise background show that the time-domain image of the signal processed by the tri-stable Stochastic resonance system is clearer and the burr is significantly reduced,which proves that the tri-stable system can effectively improve the detection performance of BPSK signals.Secondly,the system parameters determine the height of the potential barrier and the width of the potential well.The introduction of particle swarm optimization algorithm based on simulated annealing can realize the optimization of Stochastic resonance system parameters.Using an adaptive tri-stable system to detect periodic signals(sinusoidal signals,square wave signals,and harmonic signals),under optimized system parameters,the time-domain waveform can basically restore the signal to be tested,and the spectral peak at the characteristic frequency points is significantly improved.In addition,within the selected signal-to-noise ratio range of the BPSK signal,the proposed algorithm can find optimal system parameters and effectively reduce transmission error rate.Finally,a signal detection algorithm based on cascade tri-stable Stochastic resonance is proposed.Using the time-domain waveform and the spectral peak value of the characteristic frequency as the judgment index,the Stochastic resonance detection capability of periodic signals is simulated in timedomain and frequency-domain,and better output characteristics can be obtained than the single-stage tri-stable Stochastic resonance system.In addition,the simulation comparison analysis was carried out in the strong noise background,and the results confirmed that the time-domain image was clearer and the burrs were significantly reduced after the signal passed through the cascade tri-stable Stochastic resonance system.Compared with the single-stage system,the cascade tri-stable system can improve the detection performance of BPSK signals.