计算机应用 ›› 2016, Vol. 36 ›› Issue (5): 1232-1235.DOI: 10.11772/j.issn.1001-9081.2016.05.1232

• 先进计算 • 上一篇    下一篇

分步的基于模糊聚类的多雷达航迹关联算法

张树斌, 方洋旺, 雍霄驹, 彭维仕, 李伟   

  1. 空军工程大学 航空航天工程学院, 西安 710038
  • 收稿日期:2015-10-19 修回日期:2015-12-26 出版日期:2016-05-10 发布日期:2016-05-09
  • 通讯作者: 张树斌
  • 作者简介:张树斌(1991-),男,山西榆次人,硕士研究生,主要研究方向:信息融合、效能评估;方洋旺(1966-),男,安徽安庆人,教授,博士生导师,博士,主要研究方向:信息融合、效能评估、随机最优控制;雍霄驹(1987-),男,江苏南京人,博士,主要研究方向:信息融合;彭维仕(1987-),男,广西全州人,讲师,博士,主要研究方向:效能评估;李伟(1990-),男,山东菏泽人,硕士研究生,主要研究方向:效能评估。

Step-by-step multi-radar track correlation algorithm based on fuzzy clustering

ZHANG Shubin, FANG Yangwang, YONG Xiaoju, PENG Weishi, LI Wei   

  1. College of Aeronautics and Astronautics Engineering, Air Force Engineering University, Xi'an Shaanxi 710038, China
  • Received:2015-10-19 Revised:2015-12-26 Online:2016-05-10 Published:2016-05-09

摘要: 针对采用传递闭包模糊聚类的多雷达航迹关联算法运算量较大的问题,提出了分步的基于模糊聚类的多雷达航迹关联算法。首先基于欧氏距离对航迹进行预关联判断,然后通过模糊相似计算,简化了航迹相似矩阵,进而减少了相似计算与矩阵迭代的次数,最终达到了减小运算量的目的。仿真结果表明:所提算法在保证关联正确率的前提下,耗时减小了54%,有效地提高了多雷达航迹关联算法的效率。

关键词: 信息融合, 分步, 目标跟踪, 航迹关联, 模糊聚类

Abstract: Since the multi-radar track correlation algorithm based on transitive closure fuzzy clustering has high computational complexity, a step-by-step multi-radar track correlation algorithm based on fuzzy clustering was proposed. First, based on the Euclidean distance the track correlation was judged, and the track similar matrix was simplified through fuzzy similarity calculation. Furthermore, the calculation of the iterations was decreased. Finally, the computational demanding of the proposed algorithm was certainly reduced. The simulation results show that the proposed algorithm can determine targets' tracks accurately, saves 54% of time effectively with the high accuracy.

Key words: information fusion, step-by-step, target tracking, track correlation, fuzzy clustering

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