数字通信信号调制方式的自动识别
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摘要
本文在现有信号特征提取方法的基础上，提出了一些针对通信系统中常用的CW、AM、MASK、MFSK和MPSK信号进行调制类型全盲识别和参数估计的方法。
在信号识别中，选取信号的互功率谱、时频分布、MPSK信号的延迟相乘信号作为分类特征，利用模式识别中的聚类分析以及MPSK信号的基于高阶累积量构成的分类特征不变量实现了信号调制类型的自动分类。
在参数估计中，主要讨论了小波变换算法在基带信号码元宽度估计中的应用以及利用双极性基带信号的频谱估计码元宽度的可行性和有效性。
在工程实践中，用MATLAB语言实现了上述算法，理论分析和工程实践证明了本文提出算法的可行性。
Aiming at the signals including CW, AM, MASK and MPSK signals usually used in communication system, a new method is proposed on the blind-identification and parameter estimation in this paper on the basis of the methods available of feature extraction.
In the aspect of blind-identification, the mutual power spectrumx time-frequency distribution product of two delay signals are used as the features of classification .The cluster analysis and cumulant invariants of MPSK signals are used to automatically classify communication signals.
The Wavelet Transform is discussed in the code-width estimation; and the feasibility and effectiveness of the code-width estimation using the spectrum of the bipolar base-band signal are proved.
In engineering practice, the algorithms above are realized by MATLAB. Both theoretical analysis and engineering practice justify the effectiveness of the algorithms.
在信号识别中，选取信号的互功率谱、时频分布、MPSK信号的延迟相乘信号作为分类特征，利用模式识别中的聚类分析以及MPSK信号的基于高阶累积量构成的分类特征不变量实现了信号调制类型的自动分类。
在参数估计中，主要讨论了小波变换算法在基带信号码元宽度估计中的应用以及利用双极性基带信号的频谱估计码元宽度的可行性和有效性。
在工程实践中，用MATLAB语言实现了上述算法，理论分析和工程实践证明了本文提出算法的可行性。
Aiming at the signals including CW, AM, MASK and MPSK signals usually used in communication system, a new method is proposed on the blind-identification and parameter estimation in this paper on the basis of the methods available of feature extraction.
In the aspect of blind-identification, the mutual power spectrumx time-frequency distribution product of two delay signals are used as the features of classification .The cluster analysis and cumulant invariants of MPSK signals are used to automatically classify communication signals.
The Wavelet Transform is discussed in the code-width estimation; and the feasibility and effectiveness of the code-width estimation using the spectrum of the bipolar base-band signal are proved.
In engineering practice, the algorithms above are realized by MATLAB. Both theoretical analysis and engineering practice justify the effectiveness of the algorithms.
引文
[1] 张贤达，非平稳信号分析与处理[M]，第三版，北京：国防工业出版社，1998，15
[2] Azzouz, E.g.: Nandi, A.K., Automatic Modulation Recognition of Communication Signals, Kluwer Academic Publishes, Netherlands, 1996
[3] 张贤达，时间序列分析——高阶统计量方法[M]，北京：清华大学出版社，1996
[4] Yang Shaoquan: Chen Weidong, Classification of MPSK signals using cumulant invariants, Journal of Electronics[J], Vol. 19, No.1, 2002, 99-103
[5] 边肇祺：张学工，模式识别[M]，北京：清华大学出版社，2002，230-248
[6] Stéphane Mallat, A Wavelet Tour of Signal Processing[M], Academic Press, 1999
[7] 樊昌信；詹道庸：徐炳祥；吴成柯，通信原理[M]，第四版，北京：国防工业版社，1997
[8] Werter M.J., FSK Demodulation using an Adaptive Recursive Digital Filter, IEEE Trans on Signal Processing 44, (7),1996,1822-1825
[9] N R Pal, J C Bezdek, On cluster validity for the fuzzy c-mean model [J]. IEEE Trans fuzzy systems, 1995, 3(3), 370-379
[10] 高新波；裴继红等，模糊C-均值聚类算法中加权指数m的研究，电子学报[J]，Vol．28，No．4，2000，80-83
[11] K.C. Ho, W. Prokopiw; Y.T. Chan. Modulation identification of digital signals by the wavelet transform[5]. IEE Prec. Radar, Sonar Navig., Vol. 147. No. 4. August 2000, 169-176
[12] 张贤达；保铮，通信信号处理[M]，北京：国防工业出版社，2000，102-107
[13] 张贤达，时间序列分析——高阶统计量方法[M]，北京：清华大学出版社，1996
[14] Ananthram Swami, Hierarchical Digital Modulation Classification Using Cumulants, IEEE Transactions on Communications[J], VOL. 48, No. 3, MARCH 2000,416-429
[15] 章潜五，随机信号分析，西安：西安电子科技大学出版社，1990
[16] Ketterer, H.; Jondral, F.; Costa, A.H., "Classification of modulation modes using time-frequency methods," ICASSP' 99, Phoenix, AZ, pp. 2471-2474, 1999
[17] [美]科恩，时—频分析：理论与应用[M]，西安：西安交通大学出版，1998，77-111
[18] Wannsarnmaytha A; Hara S, Morinaga N, New Short-Time DFT FSK Demodulation Method for LEO Satellite Communications Systems[J]. IEICE Trans on Communications 1996, E79-B (10):1592-1597.
[19] 邹红星等，时频分析：回溯与前瞻[J]，电子学报，2000，28(9)：78-85．
[2] Azzouz, E.g.: Nandi, A.K., Automatic Modulation Recognition of Communication Signals, Kluwer Academic Publishes, Netherlands, 1996
[3] 张贤达，时间序列分析——高阶统计量方法[M]，北京：清华大学出版社，1996
[4] Yang Shaoquan: Chen Weidong, Classification of MPSK signals using cumulant invariants, Journal of Electronics[J], Vol. 19, No.1, 2002, 99-103
[5] 边肇祺：张学工，模式识别[M]，北京：清华大学出版社，2002，230-248
[6] Stéphane Mallat, A Wavelet Tour of Signal Processing[M], Academic Press, 1999
[7] 樊昌信；詹道庸：徐炳祥；吴成柯，通信原理[M]，第四版，北京：国防工业版社，1997
[8] Werter M.J., FSK Demodulation using an Adaptive Recursive Digital Filter, IEEE Trans on Signal Processing 44, (7),1996,1822-1825
[9] N R Pal, J C Bezdek, On cluster validity for the fuzzy c-mean model [J]. IEEE Trans fuzzy systems, 1995, 3(3), 370-379
[10] 高新波；裴继红等，模糊C-均值聚类算法中加权指数m的研究，电子学报[J]，Vol．28，No．4，2000，80-83
[11] K.C. Ho, W. Prokopiw; Y.T. Chan. Modulation identification of digital signals by the wavelet transform[5]. IEE Prec. Radar, Sonar Navig., Vol. 147. No. 4. August 2000, 169-176
[12] 张贤达；保铮，通信信号处理[M]，北京：国防工业出版社，2000，102-107
[13] 张贤达，时间序列分析——高阶统计量方法[M]，北京：清华大学出版社，1996
[14] Ananthram Swami, Hierarchical Digital Modulation Classification Using Cumulants, IEEE Transactions on Communications[J], VOL. 48, No. 3, MARCH 2000,416-429
[15] 章潜五，随机信号分析，西安：西安电子科技大学出版社，1990
[16] Ketterer, H.; Jondral, F.; Costa, A.H., "Classification of modulation modes using time-frequency methods," ICASSP' 99, Phoenix, AZ, pp. 2471-2474, 1999
[17] [美]科恩，时—频分析：理论与应用[M]，西安：西安交通大学出版，1998，77-111
[18] Wannsarnmaytha A; Hara S, Morinaga N, New Short-Time DFT FSK Demodulation Method for LEO Satellite Communications Systems[J]. IEICE Trans on Communications 1996, E79-B (10):1592-1597.
[19] 邹红星等，时频分析：回溯与前瞻[J]，电子学报，2000，28(9)：78-85．