应用科学学报 ›› 2009, Vol. 27 ›› Issue (2): 137-143.

• 通信工程 • 上一篇    下一篇

利用循环谱和参数统计的数字调制信号识别

朱雷1 程汉文1;2 吴乐南1   

  1. 1. 东南大学信息科学与工程学院,南京210096
    2. 防空兵指挥学院,郑州450052
  • 收稿日期:2008-09-12 修回日期:2008-11-14 出版日期:2009-04-01 发布日期:2009-04-01
  • 作者简介:吴乐南,教授,博导,研究方向:多媒体信息处理、通信信号处理,E-mail:wuln@seu.edu.cn

Identification of Digital Modulation Signals Based on Cyclic Spectral Density and Statistical Parameters

  1. 1. School of Information Science and Engineering, Southeast University, Nanjing 210096, China
    2. Air Defense Forces Command Academy, Zhengzhou 450052, China
  • Received:2008-09-12 Revised:2008-11-14 Online:2009-04-01 Published:2009-04-01

摘要:

该文利用决策理论识别常用数字信号调制方式. 该识别方法基于接收信号的循环谱和参数统计法,采用谱相关测量的频率平滑法分析数字信号在循环频率轴上的特征谱,运用参数统计法提取统计参数,用于数字调制信号识别. 最后利用决策理论,给出信号识别流程图及判决门限. 实验表明,在信噪比为5 dB的条件下,对预期调制信号2ASK, 4ASK, 2FSK, 4FSK, 4PSK, 8PSK的识别率可达90%, 说明该方法在低信噪比下识别效果良好.

关键词: 调制识别, 循环谱, 统计参数

Abstract:

 A novel method using decision-making theory is proposed to identify digital modulation signals. The method is based on the cyclic spectrum of received signals and the statistical parameters. Using the frequency domain smoothing periodogram to estimate the cyclic spectrum, the characteristic spectral density of digital modulation
signals is analyzed on the cyclic frequency axis. Statistical parameters of digital modulation signals are then
extracted. Finally, using the decision-making theory, we present a flow chart and a determination threshold for
signal recognition by computer simulation. At 5 dB SNR, identification probability of 90% for 2ASK, 4ASK, 2FSK,
4FSK, 4PSK and 8PSK can be achieved. The results show effectiveness of the method even when signals are buried in strong noise.

Key words: modulation identification, cyclic spectral density, statistical parameter

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