一种基于聚类分析的跳频信号自动分选方法

An automatic sorting method of frequency hopping signal based on clustering analysis

为了从复杂电磁环境中分选出跳频信号,提出了一种基于聚类分析的自动分选方法。该方法首先将信号特征参数估计等效成聚类分析问题,估计测量集中所包含的信号个数及各信号的特征参数,包括载频、带宽和入射方向。然后根据跳频信号的跳速范围,通过对各截获信号的特征参数进行序贯聚类,剔除干扰,获得期望的跳频信号。仿真实验表明,所提出的方法能够从复杂环境中正确地分选出跳频信号。

To sort frequency hopping signals in complex communication environment, a clustering analysis based automatic sorting method is proposed. This method considers the problem of signal feature parameters estimate as an clustering analysis problem, estimates the signal number included in measurement set, and extracts the corresponding feature parameters of each signals, such as carrier frequency, bandwidth and direction of arrival. Based on the hopping rate range of FH signals, the proposed method then uses the feature parameters of detected signals to cluster sequentially, delete interference signals and extracts the expected FH signals. Simulation results show that the proposed method is able to correctly sort FH signals in complex communication environment.