数据关联是多目标跟踪的核心部分,概率数据关联滤波(probability data association filter,PDA)算法和联合概率数据关联滤波(join tprobability data association filter,JPDA)算法是两种典型的数据关联算法。PDA方法计算量小,有较好的...数据关联是多目标跟踪的核心部分,概率数据关联滤波(probability data association filter,PDA)算法和联合概率数据关联滤波(join tprobability data association filter,JPDA)算法是两种典型的数据关联算法。PDA方法计算量小,有较好的单目标跟踪性能,但在跟踪多个目标时会发生目标的偏移和聚合现象;JPDA方法具有良好的多目标跟踪性能,但其运算量巨大而难于在工程中应用。OSPDA(the order statistics PDA)是改进型的快速算法,关联精度高并且计算量小。对这几种数据关联方法进行了分析比较,并作了仿真,指出各种算法的优缺点。展开更多
A prediction based energy-efficient target tracking protocol in wireless sensor networks(PET) was proposed for tracking a mobile target in terms of sensing and communication energy consumption.In order to maximize the...A prediction based energy-efficient target tracking protocol in wireless sensor networks(PET) was proposed for tracking a mobile target in terms of sensing and communication energy consumption.In order to maximize the lifetime of a wireless sensor network(WSN),the volume of messages and the time for neighbor discovery operations were minimized.The target was followed in a special region known as a face obtained by planarization technique in face-aware routing.An election process was conducted to choose a minimal number of appropriate sensors that are the nearest to the target and a wakeup strategy was proposed to wakeup the appropriate sensors in advance to track the target.In addition,a tracking algorithm to track a target step by step was introduced.Performance analysis and simulation results show that the proposed protocol efficiently tracks a target in WSNs and outperforms some existing protocols of target tracking with energy saving under certain ideal situations.展开更多
Multi-target tracking(MTT) is a research hotspot of wireless sensor networks at present.A self-organized dynamic cluster task allocation scheme is used to implement collaborative task allocation for MTT in WSN and a s...Multi-target tracking(MTT) is a research hotspot of wireless sensor networks at present.A self-organized dynamic cluster task allocation scheme is used to implement collaborative task allocation for MTT in WSN and a special cluster member(CM) node selection method is put forward in the scheme.An energy efficiency model was proposed under consideration of both energy consumption and remaining energy balance in the network.A tracking accuracy model based on area-sum principle was also presented through analyzing the localization accuracy of triangulation.Then,the two models mentioned above were combined to establish dynamic cluster member selection model for MTT where a comprehensive performance index function was designed to guide the CM node selection.This selection was fulfilled using genetic algorithm.Simulation results show that this method keeps both energy efficiency and tracking quality in optimal state,and also indicate the validity of genetic algorithm in implementing CM node selection.展开更多
文摘数据关联是多目标跟踪的核心部分,概率数据关联滤波(probability data association filter,PDA)算法和联合概率数据关联滤波(join tprobability data association filter,JPDA)算法是两种典型的数据关联算法。PDA方法计算量小,有较好的单目标跟踪性能,但在跟踪多个目标时会发生目标的偏移和聚合现象;JPDA方法具有良好的多目标跟踪性能,但其运算量巨大而难于在工程中应用。OSPDA(the order statistics PDA)是改进型的快速算法,关联精度高并且计算量小。对这几种数据关联方法进行了分析比较,并作了仿真,指出各种算法的优缺点。
基金Project(07JJ1010) supported by the Hunan Provincial Natural Science Foundation, ChinaProject(NCET-06-0686) supported by Program for New Century Excellent Talents in UniversityProject(IRT0661) supported by Program for Changjiang Scholars and Innovative Research Team in University
文摘A prediction based energy-efficient target tracking protocol in wireless sensor networks(PET) was proposed for tracking a mobile target in terms of sensing and communication energy consumption.In order to maximize the lifetime of a wireless sensor network(WSN),the volume of messages and the time for neighbor discovery operations were minimized.The target was followed in a special region known as a face obtained by planarization technique in face-aware routing.An election process was conducted to choose a minimal number of appropriate sensors that are the nearest to the target and a wakeup strategy was proposed to wakeup the appropriate sensors in advance to track the target.In addition,a tracking algorithm to track a target step by step was introduced.Performance analysis and simulation results show that the proposed protocol efficiently tracks a target in WSNs and outperforms some existing protocols of target tracking with energy saving under certain ideal situations.
基金Projects(90820302,60805027)supported by the National Natural Science Foundation of ChinaProject(200805330005)supported by the Research Fund for the Doctoral Program of Higher Education,ChinaProject(2009FJ4030)supported by Academician Foundation of Hunan Province,China
文摘Multi-target tracking(MTT) is a research hotspot of wireless sensor networks at present.A self-organized dynamic cluster task allocation scheme is used to implement collaborative task allocation for MTT in WSN and a special cluster member(CM) node selection method is put forward in the scheme.An energy efficiency model was proposed under consideration of both energy consumption and remaining energy balance in the network.A tracking accuracy model based on area-sum principle was also presented through analyzing the localization accuracy of triangulation.Then,the two models mentioned above were combined to establish dynamic cluster member selection model for MTT where a comprehensive performance index function was designed to guide the CM node selection.This selection was fulfilled using genetic algorithm.Simulation results show that this method keeps both energy efficiency and tracking quality in optimal state,and also indicate the validity of genetic algorithm in implementing CM node selection.
