Existing modulation recognition algorithms are reviewed. The cyclostationary of some digital communication signals such as binary amplitude shift keying ( BASK) , binary frequency shift keying ( BFSK) , binary phase shift keying ( BPSK) and quadrature phase shift keying ( QPSK) and minimum-frequency shift keying (MSK) is modeled and analyzed, and the relative characteristics of the cyclic spectrum density functions (CSDF) is extracted, including the maximum normalized amplitude on a-axis (expressed as a) , pluses on the positive /-axis (m) and pluses on the positive a-axis (n) and so on. Communication signal modulation recognition based on cyclostationary can be realized by grading decision algorithm consequently. Simulation shows, the average recognition accuracy reaching up to 90% under — 2 dB additive white Gaussian noise accounts for the reliability of the modulation recognition algorithm based on cyclostaionary.%介绍现有通信信号调制模式识别算法,对二进制幅度键控、二进制频移键控、二进制相移键控、正交相移键控、最小频移键控等几种数字通信信号的循环平稳特性建模分析,并提取出了循环谱密度函数α轴上的最大幅度归一化值a、循环谱密度函数f正半轴上的脉冲个数m、循环谱密度函数α正半轴上的脉冲个数n等相关的特征参数,通过分级判决来实现基于通信信号的循环特征的调制模式识别.仿真表明,基于循环特征的调制模式识别算法在-2 dB的加性高斯白噪声条件下,识别正确率高达90％,具有较好的可靠性.
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