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计算机工程 ›› 2011, Vol. 37 ›› Issue (6): 153-156.doi: 10.3969/j.issn.1000-3428.2011.06.053

• 人工智能及识别技术 • 上一篇    下一篇

数字通信信号调制自动识别研究

张志民，欧建平，皇甫堪   

  1. (国防科学技术大学电子科学与工程学院，长沙 410073)
  • 出版日期:2011-03-20 发布日期:2011-03-29
  • 作者简介:张志民(1971－)，男，博士研究生，主研方向：数字信号处理，人工智能与专家系统；欧建平，副教授；皇甫堪，教授、博士生导师

Research on Automatic Modulation Recognition of Digital Communication Signal

ZHANG Zhi-min, OU Jian-ping, HUANGFU Kan   

  1. (College of Electronic Science and Engineering, National University of Defense Technology, Changsha 410073, China)
  • Online:2011-03-20 Published:2011-03-29

PDF

1070

被引次数

6 | 1

摘要： 为自动识别MASK、MFSK、MPSK和MQAM信号的调制类型，提出一种瞬时幅度提取算法。该算法不需要对信号进行Hilbert变换和实现码元同步。在此基础上，提出7个特征参数和基于判决理论的调制自动识别算法。仿真结果表明，当信噪比≥8 dB时，识别算法的平均识别成功率≥97%，证明提出的瞬时幅度提取算法和调制自动识别算法均有效，可用于实际信号的在线分析。

关键词: 数字通信信号, 调制自动识别, 瞬时幅度, 特征参数, 信噪比

Abstract: In this paper, a new algorithm for extracting the instantaneous amplitudes of the intercepted signals is proposed in order to automatically recognize the modulation types of MASK, MFSK, MPSK and MQAM signals. This algorithm has no need of Hilbert transformation or symbol synchronization. On the basis of this, seven feature parameters and a modulation recognition algorithm of the aforementioned four types of signals are derived. Simulations result shows that the average modulation recognition success rate is≥97% at Signal-to-Noise Ratio(SNR)≥8 dB. It proves that the new algorithms for both the instantaneous amplitude extracting and the modulation recognition are efficient and can be used in practical online analysis.

Key words: digital communication signal, automatic modulation recognition, instantaneous amplitude, feature parameters, Signal-to-Noise Ratio(SNR)

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