基于模糊聚类的常规通信信号自动分选方法

为解决从干扰环境中自动分选出常规通信信号的问题，提出了一种基于模糊聚类的常规通信信号分选方法。该方法首先利用区分度函数确定最优的相关度阈值参数，然后利用模糊聚类算法对利用频域检测和测向得到的测量集进行信号分选，并对分选后的通信信号进行特征参数估计。实验结果表明，该算法能够在不做任何假定的条件下对常规通信信号进行正确分选，并对窄带信号的特征参数进行准确估计。

Automatic sorting of conventional communication signals based on fuzzy clustering

To automatically sort conventional communication signals in interference environment,an automatic sorting method based on fuzzy clustering algorithm is proposed. Firstly,a differentiating function is used to calculate the optimal value of relevance threshold. Secondly,the fuzzy clustering algorithm is used to classify the signals included in measurement set derived from the result of frequency detection and direction finding. Finally,the basic characteristic parameters of each signal are estimated. Simulation results show that the algorithm can sort the conventional communication signals accurately in interference surroundings accurately without any assumption,and can estimate the characteristic parameters of narrow band signals correctly.