Journal of Systems Engineering and Electronics ›› 2012, Vol. 34 ›› Issue (1): 160-167.doi: 10.3969/j.issn.1001-506X.2012.01.30

• 通信与网络 • 上一篇    下一篇

网络协同跟踪下广义分布式航迹关联方法

杨海燕1,2, 王琳2, 尤政1   

  1. 1. 清华大学精密仪器与机械学系, 北京 100084;
    2. 空军工程大学工程学院, 陕西 西安 710038
  • 出版日期:2012-01-13 发布日期:2010-01-03

Generalized distributed track-to-track association algorithm for collaborative network tracking

YANG Haiyan1,2, WANG Lin2, YOU Zheng1   

  1. 1. Department of Precision Instruments and Mechanology, Tsinghua University, Beijing 100084, China;
     2. Engineering College, Air Force Engineering University, Xi’an 710038, China
  • Online:2012-01-13 Published:2010-01-03

摘要:

针对协同网络下的多目标跟踪问题,提出了一种广义分布式航迹关联算法。首先对序贯航迹关联准则进行分析,构造了广义分布式航迹全配对似然函数以及航迹关联统计量;在此基础上,建立广义航迹关联的数学模型,从而将分布式航迹关联转化为多维分配问题;然后利用改进免疫算法来寻求最理想的航迹关联。在航迹关联过程中,先利用chi方分布的假设检验来排除明显不相关的关联组合,再通过计算免疫抗体的适应值来确定多节点航迹间的关联关系;最后利用航迹关联评价指标对所提出的方法进行评估。仿真结果显示,该方法在密集目标环境下具有较好的关联稳定性,与序贯航迹关联方法相比,关联效果得到明显改善。

Abstract:

A generalized distributed track-to-track  association method is proposed for multiple targets tracking in collaborative sensor network. Firstly, by analyzing the traditional sequence  track-to-track  association rules, all pairwise likelihood function and generalized  track-to-track  association statistic of the distributed tracking are constructed. On the basis of that, the mathematical model of the generalized track-to-track  association is established. Then the distributed  track-to-track  association question is translated into the multiple dimension assignment. Secondly, the optimal association relationship among tracks is searched by using the improved  immunity algorithm. The whole  track-to-track  association course includes two stages. At first, the unrelated track combination is eliminated by using the chisquare distribution hypothesis test, and then the multiple sensors multiple tracks association relationship is confirmed according to the immunity antibody fitness. Finally, the proposed method is evaluated by utilizing some track-to-track  association performance parameters. Simulation results show that the association stability and the association effect of the new method are improved obviously compared with the traditional sequence pairwise association method.