频谱监测中的多频随机共振检测
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1. 电子科技大学 成都 611731; 2. 国家无线电监测中心成都监测站 成都 611136;3. 国家无线电监测中心云南监测站 昆明 650031

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TP2

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Multifrequency stochastic resonance detection in spectrum monitoring
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1. University of Electronic Science and Technology, Chengdu 611731, China;2. The State Radio_monitoring_center of Chengdu, Chengdu 611136, China; 3. The State Radio_monitoring_center of Yunnan, Kunming 650031, China

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    摘要:

    基于频段分离思想设计能够完成频谱监测中多频微弱信号的双稳态随机共振检测方案。使用归一化尺度变换对高频段范围内周期信号进行随机共振检测仿真实验;针对随机共振方法对多频信号检测的局限性,利用小波变换频段分离的特性,将小波变换与归一化随机共振相结合,进行多频微弱信号检测仿真实验。仿真结果表明,结合了小波变换的归一化随机共振的方案能够检测出待测频段内的多频微弱周期信号。

    Abstract:

    This paper design a detection program for multifrequency weak signal based on the method of bistable stochastic resonance with the thought of separation of frequency band in spectrum monitoring. Normalized scale transformation is used to complete the simulation of stochastic resonance detection of periodic signals in high frequency range. Aiming at the limitation of the stochastic resonance method for the multifrequency signal detection, the wavelet transform and the normalized stochastic resonance are conbined to achieve the multifrequency weak signal detection simulation experiment with the characteristic of wavelet transform that can separate the frequency band. The simulation results show that the normalized stochastic resonance scheme combined with the wavelet transform can detect the multifrequency weak periodic signal in the frequency band to be measured.

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张伟达,陈良,梅芳,金燕华.频谱监测中的多频随机共振检测[J].国外电子测量技术,2017,36(9):9-12

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  • 在线发布日期: 2017-11-09
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