华南理工大学学报(自然科学版) ›› 2012, Vol. 40 ›› Issue (3): 49-56.

• 电子、通信与自动控制 • 上一篇    下一篇

协同网络下分布式跟踪的动态传感器管理

杨海燕1 尤政1 王琳2   

  1. 1.清华大学 精密仪器与机械学系,北京 100084; 2.总参陆航研究所,北京 101121
  • 收稿日期:2011-07-26 修回日期:2011-10-21 出版日期:2012-03-25 发布日期:2012-02-01
  • 通信作者: 杨海燕(1972-) ,女,博士生,主要从事传感器网络资源管理研究. E-mail:yanghy07@mails.tsinghua.edu.cn
  • 作者简介:杨海燕(1972-) ,女,博士生,主要从事传感器网络资源管理研究.
  • 基金资助:

    国家“863”计划项目( 2010AA8090514C) ; 航空科学基金资助项目( 20095196012)

Dynamic Sensor Management for Distributed Tracking in Collaborative Network

Yang Hai-yan1  You Zheng1  Wang Lin2   

  1. 1.Department of Precision Instruments and Mechanology,Tsinghua University,Beijing 100084,China; 2.Army Aviation Research Institute,General Staff of PLA,Beijing 101121,China
  • Received:2011-07-26 Revised:2011-10-21 Online:2012-03-25 Published:2012-02-01
  • Contact: 杨海燕(1972-) ,女,博士生,主要从事传感器网络资源管理研究. E-mail:yanghy07@mails.tsinghua.edu.cn
  • About author:杨海燕(1972-) ,女,博士生,主要从事传感器网络资源管理研究.
  • Supported by:

    国家“863”计划项目( 2010AA8090514C) ; 航空科学基金资助项目( 20095196012)

摘要: 协同网络系统采用分等级的分布式信息处理结构,在实现对杂波中多目标精确跟踪时,需要考虑量测起源不确定性问题和传感器对目标及局部融合中心的同时分配问题.针对上述问题,提出一种适用于分布式跟踪的动态传感器管理方法.首先以修正Riccati方程的解作为目标跟踪性能的评价标准,据此构建传感器管理的目标函数;然后在求解过程中,提出一种分层优化策略,利用蚁群算法实时求近似优解,最后基于分布式融合算法获取多目标的最优跟踪轨迹.仿真显示,与另两种传感器管理方法比较,所提方法具有更高的目标跟踪精度和网络资源利用率.

关键词: 协同网络, 分布式跟踪, 传感器管理, 修正Riccati差分方程

Abstract:

In the accurate tracking of multiple targets in clutter by using a collaborative network system with hierarchical and distributed information processing structure,both the measurement uncertainty and the sensor assignment to the target as well as the local fusion centers must be taken into consideration. In order to solve these problems,a dynamic sensor management method for distributed tracking is proposed. In this method,first,the criteria to evaluate the tracking performance are determined based on the solution to the modified Riccati difference equation,with which the objective function of the dynamic sensor management is constructed. Then,according to a hierarchical optimization strategy and by using the improved ant colony algorithm,an approximate optimal solution is obtained in real time. Finally,the optimal multi-target tracking trajectories are obtained by using a distributed fusion algorithm. Simulated results indicate that,as compared with the two dynamic sensor management methods,namely NN-Clustering and MV-Clustering,the proposed method is of higher multi-target tracking accuracy and higher utilization rate of network resource.

Key words: collaborative network, distributed tracking, sensor management, modified Riccati difference equation

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