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非高斯水下噪声中微弱线谱信号的符号函数型随机共振检测
引用本文:董华玉,张晓兵,玄兆林.非高斯水下噪声中微弱线谱信号的符号函数型随机共振检测[J].兵工学报,2008,29(3):318-322.
作者姓名:董华玉  张晓兵  玄兆林
作者单位:海军工程大学,兵器工程系,湖北,武汉,430033;海军工程大学,兵器工程系,湖北,武汉,430033;海军工程大学,兵器工程系,湖北,武汉,430033
摘    要:采用符号函数作为随机共振模型,对非高斯水下噪声环境中的信号检测进行研究,分析了其检测性能。与Langevin型的随机共振相比,该模型具有更高的局部信噪比增益和更宽的频率适应范围。数值仿真表明,噪声的非高斯性越明显,符号函数型随机共振系统的性能表现越优异。由实测数据对所采用的随机共振的有效性进行了验证。

关 键 词:信息处理技术  随机共振  微弱信号  线谱  非线性双稳态  局部信噪比增益  混合高斯分布
文章编号:1000-1093(2008)03-0318-05
修稿时间:2006年10月8日

Weak Line Spectrum Detection Based on Sign Function Type Stochastic Resonance in Non-Gaussian Marine Noise
DONG Huayu,ZHANG Xiao-bing,XUAN Zhao-lin.Weak Line Spectrum Detection Based on Sign Function Type Stochastic Resonance in Non-Gaussian Marine Noise[J].Acta Armamentarii,2008,29(3):318-322.
Authors:DONG Huayu  ZHANG Xiao-bing  XUAN Zhao-lin
Affiliation:Department of Weaponry Engineering, Naval University of Engineering, Wuhan 430033,Hubei, China
Abstract:Taking sign function as a stochastic resonance (SR) moael, we researched a signal detection method in the non-Gaussian underwater noise environment and analyzed tlie performance of the detec?tor. In contrast with SR based on Langevin function, the proposed model have a higher local signal-to- noise ratio gain and can be used in a wider frequency range. Numerical simulation indicates that, the more evident the non-Gaussian characteristics of noise are, the more excellent the performance of the detection method based on sign function SR is. The real data certify the proposed SR’s validity.
Keywords:information processing    stochastic resonance    weak signal    line spectrum    nonlinear Dista- Dility    local signal-to-noise ratio gain    Gaussian mixture distribution  
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