Weak Signal Detection Based On The Theory Of Stochastic Resonance

Weak signal detection is a traditional investigative task based on strong noise background, which has extensive applications in communication,radar,ocean,biomedicine and other many areas. Recently incessant development of nonlinear science, especially proposed stochastic resonance theory, creates a novel idea for weak signal detection.Stochastic resonance is the phenomenon of enhancement of input signal by certain nonlinear systems resulting from the addition of noise to the system, because of noise energy moving to signal, enhanced output Signal-radio-Noise can distill characteristic information of weak signal, Bi-stable stochastic resonance system as model is studied in the thesis, studious labors and gains are as follows:Firstly, A numerical algorithm called variable step stochastic resonance is proposed toward adiabatic elimination stochastic resonance within small parameters, which can(?)meet actual requirement. The proposed method can adapt to weak signal detection in both small and large parameters by adjusting the calculating step, which promotes stochastic resonance(?)development. Previously making use of stochastic resonance to gain detected signals? frequency information, the thesis analyzed how to detect detected signals? amplitude based on proposed algorithm, describing basic process to detect signal(?)amplitude;Secondly, The thesis discussed how to dispose several mixed signals conditions, mixed signals? condition with high and low frequencies is primary investigative emphases, the thesis described basic disposal process;Thirdly, In order to make use of stochastic resonance disposing high dimension signals, the thesis had done some studies and gained some effects. the study explored future application of stochastic resonance(?) technology disposing high dimension signals.The thesis had also done simulation experiments to above algorithms by building simulation model of bi-stable system, approving rationality of stochastic resonance theory and method.