基于无线传感器网络的分布式处理目标跟踪系统  

Distributed Processing Target Tracking System Based on Wireless Sensor Networks

作　　者：危阜胜[1] 胥布工[1] 高焕丽[1] 谢立华[1,2] 

机构地区：[1]华南理工大学自动化科学与工程学院,广州510640 [2]南洋理工大学电子与电气工程学院,新加坡639798

出　　处：《传感技术学报》2009年第10期1498-1503,共6页Chinese Journal of Sensors and Actuators

基　　金：NSFC-广东联合基金重点项目资助(U0735003);海外及港澳学者合作研究基金资助(60828006)

摘　　要：系统使用超声波传感器和扩展卡尔曼滤波对无线传感器网络中的移动单目标进行定位跟踪。节点嵌入式应用程序采用TinyOS/nesC[1]编程实现,采用Labview进行应用层开发。为了优化网络的能耗以延长网络寿命,提出了两种在分布式传感器网络中局部节点自适应选择任务节点[2]的方法。实验结果验证了扩展卡尔曼算法的正确性,并比较了这两种任务节点选择调度方法的跟踪性能,得出了基于候选节点协方差矩阵最小迹的任务节点选择调度方式在目标丢失率和跟踪精度综合考虑的基础上性能更优。This paper discusses the development of a Wireless Sensor Networks（WSN） based target tracking platform. The platform involves ultrasound sensors for target detection and Extended Kalman Filter （EKF）for tracking a single target. The embedded application is implemented by TinyOS/nesC, and Labview is used to develop the Graphical User Interface（GUI）. In order to optimize the energy consumption and to prolong the lifetime of networks, two schemes of local tasking node selection in a self-adaptive way are given in the decentralized sensor networks. The experiment results validate the correctness of the Extended Kalman Filtering arithmetic and draw a conclusion that the least trace of covariance matrix scheme has better performance when considering the target loss rate and the tracking precision.

关 键 词：无线传感器网络 目标跟踪 扩展卡尔曼滤波 分布式处理 自适应调度 

分 类 号：TP302.1[自动化与计算机技术—计算机系统结构]