Application of parameter-tuning stochastic resonance for detecting weak signal with ultrahigh frequency
HAO Jing1,2, DU Taihang1, JIANG Chundong1, SUN Shuguang1, FU Chao3
1. School of Control Science and Engineering, Hebei University of Technology, Tianjin 300130, China; 2. Department of Computer Application, Shijiazhuang Information Engineering Vocational College, Shijiazhuang Hebei 050035, China; 3. Department of Electronics, Hebei Normal University, Shijiazhuang Hebei 050024, China
Abstract：Aiming at the problem that common nonlinear Stochastic Resonance (SR) system is subject to the restriction of small parameter and is failure to detect the high frequency weak signal, a new detection method of parameter-tuning SR for weak signal with high frequency was proposed. Firstly, the relationship between the damping coefficient and the signal frequency was derived in a bistable system, and by using Kramers rate for analysis, the influence of changing damping coefficient on the SR of the system was verified. Then, the influence of SR phenomenon produced by system shape parameters was deduced, the SR of high frequency weak signal was realized through adjusting the damping coefficient and the system shape parameters, and the effect of output spectrum characteristics of the system and different sampling frequency was discussed, the stability of the algorithm was verified by the results. Finally, using the received actual signals with noise as experimental research data, the experimental results show that ultrahigh frequency weak signal under strong noise background can be extracted effectively and steadily using the strategy even when the signal frequency reaches MHz and GHz. The proposed method extends the application field of SR principle of weak signal detection.
郝静, 杜太行, 江春冬, 孙曙光, 付超. 调参随机共振在超高频微弱信号检测中的应用[J]. 计算机应用, 2016, 36(9): 2374-2380.
HAO Jing, DU Taihang, JIANG Chundong, SUN Shuguang, FU Chao. Application of parameter-tuning stochastic resonance for detecting weak signal with ultrahigh frequency. Journal of Computer Applications, 2016, 36(9): 2374-2380.
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2016, Vol. 36 
