基于统计特征主分量的信号调制识别

Modulation Recognition of Signal Based on Statistical Principal Component Feature Parameters

  • 摘要: 采用数字信号处理方法提取待识别信号的瞬时特征统计参量,利用多元统计的主分量分析方法对特征参量进行其主分量组合,以消除特征参量间的相关性和压缩特征向量的维数,并采用统计模式识别的模板匹配判决进行信号调制方式的自动识别,模拟结果证实了此方法的有效性和高识别率。

     

    Abstract: The instantaneous feature parameters of received signal are extracted using digital signal processing, the eliminating correlation and dimensionality reduction for these feature parameters are realized using the principal component analysis approach. The classification and recognition of modulation of signal are designed by template matching of statistical pattern recognition. The simulation results show the approach proposed in this paper is efficient.

     

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