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计算机工程 ›› 2011, Vol. 37 ›› Issue (16): 27-29. doi: 10.3969/j.issn.1000-3428.2011.16.009

• 博士论文 • 上一篇    下一篇

基于功率控制的多节点协同目标跟踪算法

韩 屏 1,王怀兴 2,孔祥斌 3   

  1. (1. 武汉理工大学信息工程学院,武汉 430070;2. 湖北第二师范学院物理与电子信息学院,武汉 430205;3. 湖北工业大学电气与电子工业学院,武汉 430068)
  • 收稿日期:2010-12-10 出版日期:2011-08-20 发布日期:2011-08-20
  • 作者简介:韩 屏(1980-),男,讲师、博士,主研方向:无线传感器网络,光纤传感技术;王怀兴、孔祥斌,硕士
  • 基金资助:

    国家自然科学基金资助项目(60773212);教育部基金资助重点项目(107130)

Multinode Collaborative Algorithm for Target Tracking Based on Power Control

HAN Ping 1, WANG Huai-xing 2, KONG Xiang-bin 3   

  1. (1. School of Information Engineering, Wuhan University of Technology, Wuhan 430070, China;2. School of Physical and Electrical Information, Hubei University of Education, Wuhan 430205, China;3. School of Electrical and Electronic Industry, Hubei University of Industry, Wuhan 430068, China)
  • Received:2010-12-10 Online:2011-08-20 Published:2011-08-20

摘要: 为适应资源有限的无线传感器网络节点的目标跟踪需求,并在保证跟踪性能的同时降低算法复杂度,提出一种功率控制和多节点协调(PC&MC)目标跟踪算法。借鉴Rao-Blackwellized技术,实现多节点协同作业以保证对动态目标的跟踪精度,采用基于连续/离散混合模型的准高斯粒子滤波器完成对目标的跟踪,在跟踪过程中使用功率控制机制指挥协同节点工作。通过仿真对算法的性能进行验证,结果表明PC&MC算法适用于存储、计算等各项资源都有限的无线传感器节点,目标跟踪精度较高。

关键词: 无线传感器网络, 混合模型, 目标跟踪, 准高斯粒子滤波器, 功率控制

Abstract: In order to fit the requests of Wireless Sensor Network(WSN) nodes with finite resource, a Power Control and Multinode Collaborative (PC&MC) algorithm for target tracking is proposed, which can guarantee the performance of tracking with less complexity. Multinode collaborative working is realized to ensure the precision of mobile target tracking utilizing the design ideal of Rao-Blackwellized technology. The Quasi-Gauss Particle Filter(Q-GPF) based on continuous/discrete mixed model is used to complete target tracking, and power control is used to direct the working of collaborative nodes. The performance of PC&MC algorithm is verified by simulation, the simulating data can prove that PC&MC algorithm suits for WSN nodes, whose resources such as storage and computation are limited, and the precision of target tracking is well improved.

Key words: Wireless Sensor Network(WSN), mixed model, target tracking, Quasi-Gauss Particle Filter(Q-GPF), power control

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