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基于无线传感器网络的车辆跟踪算法设计与分析
引用本文:肖硕,魏学业,王钰.基于无线传感器网络的车辆跟踪算法设计与分析[J].北京交通大学学报(自然科学版),2008,32(5).
作者姓名:肖硕  魏学业  王钰
作者单位:北京交通大学电子信息工程学院,北京,100044;北京交通大学电子信息工程学院,北京,100044;北京交通大学电子信息工程学院,北京,100044
摘    要:设计了一种基于传感器网络的车辆跟踪方法,为了达到降低能量消耗的目的,文中结合车辆动力学的知识,减小跟踪区域,减少活动节点个数.现实中,车辆运动带有目的性,车辆的位置和速度在时间上具有相关性,为此本论文采用GM模型来预测车辆下一时刻的位置,依据车辆位置来更新跟踪区域,确保移动目标始终处于跟踪区域内.仿真结果表明,相对于OCR法,本方法降低了22%的能量开支.

关 键 词:无线传感网络  车辆追踪  车辆动力学  GM预测模型

Design and Analysis of Vehicle Tracking Algorithms Based on Wireless Sensor Networks
XIAO Shuo,WEI Xueye,WANG Yu.Design and Analysis of Vehicle Tracking Algorithms Based on Wireless Sensor Networks[J].JOURNAL OF BEIJING JIAOTONG UNIVERSITY,2008,32(5).
Authors:XIAO Shuo  WEI Xueye  WANG Yu
Abstract:A vehicle tracking scheme based on wireless sensor networks(WSNs)was designed in this paper.In order to reduce energy dissipation,the method used in this paper minimizes the tracking region and decreases number of active nodes with considering vehicular kinematics.Because the vehicle usually travels with a destination in reality,therefore vehicle's location and velocity are likely to be correlated with its current location and velocity.So the gauss-markov mobility model to predict the vehicle position was introduced,the tracking region was updated by the location of vehicle to keep the mobile target in the tracking region.The simulation results shown that this scheme can reduce energy overhead by 22% compared with OCR.
Keywords:wireless sensor networks  vehicle tracking  vehicular kinematics  gauss-markov(GM)prediction model
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