J4 ›› 2012, Vol. 39 ›› Issue (1): 67-74.doi: 10.3969/j.issn.1001-2400.2012.01.013

• 研究论文 • 上一篇    下一篇

一种新的数据融合航迹关联算法

权义宁1;姜振1;黄晓冬2;李伟峰3   

  1. (1. 西安电子科技大学 计算机学院,陕西 西安  710071;
    2. 海军航空工程学院 软件中心,山东 烟台  264001;
    3. 西安飞机国际制造股份有限公司,陕西 西安  710089)
  • 收稿日期:2010-11-18 出版日期:2012-02-20 发布日期:2012-04-06
  • 通讯作者: 权义宁
  • 作者简介:权义宁(1969-),男,副教授,博士,E-mail: ynquan@mail.xidian.edu.cn.
  • 基金资助:

    陕西省自然科学基础研究计划资助项目(2010JM8027)

Study of a new track correlation algorithm in data fusion

QUAN Yining1;JIANG Zhen1;HUANG Xiaodong2;LI Weifeng3
  

  1. (1. School of Computer Science and Technology, Xidian Univ., Xi'an  710071, China;
    2. Software Center, Naval Aeronautical Engineering Institute, Yantai  264001, China;
    3. Xi'an Aircraft International Corp., Xi'an  710089, China)
  • Received:2010-11-18 Online:2012-02-20 Published:2012-04-06
  • Contact: QUAN Yining

摘要:

最近邻域经典算法在求解航迹关联问题时,由于过度依赖特征阈值以及缺乏全局性考虑,在航迹密度较高的情况下容易出现错误关联.针对这一问题,引入全局搜索策略并采用动态规划和跟踪门技术,提出了一种新的全局最优航迹关联算法.在真实的海上目标航迹关联环境下对两种算法进行了实现,与最近邻域算法相比,新算法不仅获得了较高的关联正确率,同时减少了关联结果对特征阈值的依赖.

关键词: 数据融合, 航迹关联, 全局搜索, 动态规划, 跟踪门

Abstract:

Because of being highly dependent on the threshold and lacking the consideration of global solutions, the Nearest Neighbors Algorithm(NNA) will make some mistakes when the density of targets is high. To solve this problem, global search strategy, gating and dynamic programming are used to build a new correlation algorithm-the Global Best Track Correlation Algorithm(GBTCA). In two experiments, both of the two algorithms are run and compared to NNA, GBTCA, which shows that the new algorithm has a higher correct correlation rate and is less dependent on threshold values.

Key words: data fusion, track correlation, global search, dynamic programming, gating

中图分类号: 

  • TP391