Research On Stochastic Resonance Of The Weak Leaked Electromagnetic Signals` Detection In Digital System

Digital system may produce weak leaking electromagnetic signals, since the electromagnetic radiation of the device clock circuit and the vibration. This weak electromagnetic signals'detection has important practical significance. Different from the traditional signal detection method, stochastic resonance technology can bring part of the noise energy transform into signal energy, so that it can enhance the signal intensity, improve signal SNR, and achieve the purpose of the weak signal detection. In this paper, stochastic resonance theory is used in the detection of weak leaking electromagnetic signals of digital system, and weak electromagnetic signal feature information is extracted from complex noise background.Based on the comparison and analysis of the traditional adaptive algorithm, in this paper, a kind of improved adaptive algorithm based on stochastic resonance theory is designed to be the weak signal extraction algorithm, and the simulation results are analyzed and discussed. This algorithm uses signal output SNR as detecting indicator, the value of weight vector in the algorithm can be adjusted dynamically to guide the stochastic resonance effect happen, so that the signal amplitude can be strengthened. The simulation results show that, after being processed by this algorithm, the signal is successfully isolated from the noise background.Based on stochastic resonance theory and bi-stable structure model, in this paper, a set of signal testing system is designed as signal processing and analysis module in the detection platform of weak leaking electromagnetic signals of digital system. Adaptive stochastic resonance algorithm designed above is embedded in the algorithm module of this testing system. Matlab software is used for the model structure design simulation of the signal testing system, and the measured data of the leaking signals produced by two sets of digital system is analyzed and processed, and prove the effectiveness of this signal testing system.