J4 ›› 2011, Vol. 38 ›› Issue (4): 148-153.doi: 10.3969/j.issn.1001-2400.2011.04.027

• 研究论文 • 上一篇    下一篇

一种低复杂度的雷达信号分选方法

王世强;张登福;毕笃彦;雍霄驹   

  1. (空军工程大学 工程学院,陕西 西安  710038)
  • 收稿日期:2010-11-14 出版日期:2011-08-20 发布日期:2011-09-28
  • 通讯作者: 王世强
  • 作者简介:王世强(1982-),男,西安空军工程大学博士研究生,E-mail: wunsicon@163.com.
  • 基金资助:

    国家部委科技重点实验资助项目(9140C610301080C6106)

Novel radar signal sorting method with low complexity

WANG Shiqiang;ZHANG Dengfu;BI Duyan;YONG Xiaoju   

  1. (Institute of Engineering, AFEU, Xi'an  710038, China)
  • Received:2010-11-14 Online:2011-08-20 Published:2011-09-28
  • Contact: WANG Shiqiang

摘要:

针对现有支持向量聚类算法在雷达信号分选应用中复杂度高、用传统有效性指标难以描述最佳分选效果的问题,研究了基于锥面聚类分配的支持向量聚类算法;利用该算法依赖于特征空间和数据空间近似覆盖的特性,避免了邻接矩阵的计算.提出了基于相似熵的有效性验证指标,应用信息熵的理论描述了类内聚集性和类间分离性.仿真结果表明,该方法在保证分选正确率的同时,可以有效降低计算复杂度,在一定程度上满足了情报侦察系统的实时性和准确性要求,具有较强的实用价值.

关键词: 信号分选, 聚类算法, 支持向量聚类, 锥面聚类分配, 相似熵, 有效性验证, 分离性

Abstract:

The radar signal sorting method based on the traditional Support Vector Clustering(SVC) algorithm leads to a high time complexity, and the traditional validity index can not indicate the best sorting result efficiently. Aimed at the problem, a new sorting method is presented based on the Cone Cluster Labeling(CCL) method for the SVC algorithm. The CCL method relies on the theory of approximate coverings both in teature space and data space. And a new cluster validity index, Similitude Entropy (SE) index,is proposed which assesses the compactness and separation of clusters using the information entropy theory. The problem mentioned above can be resolved well with the proposed method. Experimental results show that the strategy can improve efficiency without sacrificing sorting accuracy. Meanwhile the proposed method can meet the real-time and accuracy requirements of the ELINT system to some extent and is of good practical value.

Key words: signal sorting, clustering algorithms, support vector clustering, cone cluster labeling, similitude entropy, verification, separation

中图分类号: 

  • TN 974