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Radar signal recognition based on time-frequency representations and multidimensional probability density function estimator

机译:基于时频表示和多维概率密度函数估计器的雷达信号识别

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A radar signal recognition can be accomplished by exploiting the particular features of a radar signal observed in presence of noise. The features are the result of slight radar component variations and acts as an individual signature. The paper describes radar signal recognition algorithm based on time frequency analysis, noise reduction and statistical classification procedures. The proposed method is based on the Wigner-Ville Distribution with using a two-dimensional denoising filter which is followed by a probability density function estimator which extracts the features vector. Finally the statistical classifier is used for the radar signal recognition. The numerical simulation results for the P4-coded signals are presented.
机译:雷达信号识别可以通过利用在存在噪声的情况下观察到的雷达信号的特定功能来实现。这些功能是雷达组件略有变化的结果,可作为单独的标志。本文介绍了基于时频分析,降噪和统计分类程序的雷达信号识别算法。所提出的方法基于Wigner-Ville分布,其中使用了二维降噪滤波器,其后是提取特征向量的概率密度函数估计器。最后,将统计分类器用于雷达信号识别。给出了P4编码信号的数值仿真结果。

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