一种异常无线电通信信号实时检测方法

Abnormal radio signal real-time detecting method

采用构造型神经网络对大规模通信信号进行聚类,提出了时幅关联比较法快速检测异常无线电信号。聚类中,在初始聚类粒度选择上进行了改进,采用增加初始聚类粒度权系数的方法,提高了聚类效率;异常信号检测中,提出了时间与信号功率谱幅度联合关联的时幅关联比较法,快速地检测异常信号。实验结果验证了该方法的可行性和实效性。

In this paper,the constructive neural networks is used to cluster large-scale communication signals,then a time-spectrum correlation method to detect abnormal radio signals is proposed.In the clustering,a method of adding the weight of initial clustering granularity is used to improve the covering clustering algorithm,which can enhance clustering performance.In the detecting of abnormal radio signal,the time and spectrum characters of a signal are related to find whether the signal is abnormal.The experimental results show the feasibility and effectiveness of this method.