摘要
提出了一种基于高阶累积量和星座图的数字调制信号识别的算法.该算法利用信号的高阶累积量,并结合改进的星座图聚类分析法,采用一种分层的多分类器对信号进行分类.算法中所选用的特征参数对信号的幅度和相位抖动不敏感,同时能有效地抑制加性高斯噪声.仿真结果表明,在接收数据长度为800和信噪比不低于6 dB的情况下,该算法对不同调制信号的正确识别率均达到93%以上.
A recognition algorithm of digital modulation signals based on high order cumulants（HOC） and constellation was presented,which connected high order cumulants with improved constellation clustering and adopts hierarchical multiclass classifier to identify digital signal types.The feature parameters were invariant with the respect to difference of amplitude and phase,and they could suppress additive Gaussian noise effectively.Simulations showed that the success rate was over 93% for recognition of the different modulations when RSN is not lower than 6 dB with 800 samples.
出处
《哈尔滨商业大学学报（自然科学版）》
CAS
2011年第4期609-613,共5页
Journal of Harbin University of Commerce：Natural Sciences Edition
基金
国家教学专项基金资助项目(00208002063504)
关键词
高阶累积量
星座图聚类
调制识别
傅里叶变换
分层分类器
high order cumulant； constellation clustering； modulation recognition； Fourier transform； hierarchical classifier；
