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引用本文格式: 刘志芳,李健. 低采样率非线性随机共振微弱信号检测 [J]. 四川大学学报: 自然科学版, 2015, 52: 1267~1271.
 
低采样率非线性随机共振微弱信号检测
Weak characteristic signal detection based on nonlinear monostable stochastic resonance with lower sampling frequencyfrequency;Interpolation
摘要点击 636  全文点击 578  投稿时间:2014-12-08  
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DOI编号   
中文关键词   .随机共振  弱信号检测  采样率  插值
英文关键词   Stochastic resonance  Signal detection  Sampling
基金项目   国家自然科学基金资助项目(61271330); 高等学校博士学科点专项科研基金资助项目
作者单位
刘志芳 四川大学电子信息学院 
李健 四川大学电子信息学院 
中文摘要
    传统的随机共振方法处理微弱信号要求很高的采样率(信号最高频率的50倍以上).本文提出了一种在采样率较低的情况下利用非线性随机共振系统检测弱信号的方法,并推导了参数归一化单稳随机共振系统模型,极大地降低了利用随机共振检测弱信号的采样率.通过插值处理等效地提升低采样率下样本信号的采样率,并将插值后的信号送入参数归一化单稳系统进行随机共振处理,可在较低的采样率下提取特征信号.仿真结果表明,在采样率仅为信号最高频率的6倍时,在输入信噪比为-20dB的强噪声背景下,利用本方法可实现弱信号的检测
英文摘要
    In order to extract the target signal in the strong noise background at a lower sampling frequency, a method based on interpolation was proposed for the oversampling problem of using stochastic resonance to process signal and the system model of parameter normalized monostable stochastic resonance system was derived in this paper. Firstly, via interpolator to enhance the sampling rate of the sample signal equivalently, then took the interpolated signal as the input of the normalized monostable system and processed it. The simulation results indicated that: while the sampling frequency was only 6 times the highest frequency feature signals’ under the 1strong noise background of input SNR (Signal to Noise Ratio) is-20 dB, this method can be used to achieve the purpose of detecting signal which submerged in heavy noise.

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