北京邮电大学学报

  • EI核心期刊

北京邮电大学学报 ›› 2009, Vol. 32 ›› Issue (2): 80-84.doi: 10.13190/jbupt.200902.80.wangb

• 论文 • 上一篇    下一篇

基于聚类的跳频信号分选

王斌 陈秋华 王翠柏   

  1. 信息工程大学 信息工程大学
  • 收稿日期:2008-08-14 修回日期:2008-10-23 出版日期:2009-04-28 发布日期:2009-04-28
  • 通讯作者: 陈秋华

Qiu-Hua CHEN Bin WANG Cui-Bai WANG   

  • Received:2008-08-14 Revised:2008-10-23 Online:2009-04-28 Published:2009-04-28
  • Contact: Qiu-Hua CHEN

摘要:

为了对跳频信号进行分选,主要研究了聚类算法. 首先对KHM算法进行改进,得到了对随机初始化中心不敏感的聚类算法,然后利用已有的聚类有效性评价函数获得最佳聚类数的范围,并提出了在此范围内寻找最佳聚类数的算法. 结合改进的KHM算法和聚类个数估计方法,利用信号持续时间、方位信息和功率,对跳频信号进行分选,实验表明,该算法能正确地分选出跳频信号.

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Abstract:

In order to identify frequency hopping signals, clustering algorithms are mainly studied. The K HarmonicMeans (KHM) algorithm is first modified to achieve insensitivity for random initialization of clustering centers. An existing cluster validity function is used to acquire the range of the optimum clustering number. A new method to estimate the exact optimum clustering number is proposed. Combining the improved algorithm of KHM with the method proposed to estimate the clustering number, frequency hopping signals are identified with easyknown signals' durations, directions and power. The proposed algorithm is shown good in performance.

Key words: frequency hopping signals, identification, clustering, K Harmonic-Means clustering