基于KHM聚类算法的跳频信号分选

针对跳频信号分选,主要研究了聚类算法及利用直方图来预估计聚类数目及初始中心的方法.首先对直方图方法进行改进,得到了对跳频信号参数估计值误差不敏感的方法,其次对初始化中心不敏感的KHM聚类算法进行改进并聚类,最后提出了通过定义类内距类间距的方法来确定最佳聚类数的算法.通过改进的KHM算法和估计聚类个数方法,利用跳频信号参...

Identification of frequency hopping signals based on clustering

In order to identify frequency hopping signals,clustering algorithms and searching parameter＇ histogram peak values are studied.The histogram algorithm is firstly modified to achieve insensitivity to the estimating error of frequency hopping signal parameters.Secondly,the K Harmonic-Means（KHM） algorithm is modified to achieve insen-sitivity to the random initialization of clustering centers.And finally,a new method of estimating the exact optimum clustering number is proposed.Combining the improved KHM algorithm with the method of estimating the clustering number,the frequency hopping signals can be identified with easily known signals＇ durations,directions and powers.The proposed algorithm is shown good in performance.