[1]庞小双,王邢波. 基于PCRLB的目标跟踪节点选择算法[J].计算机技术与发展,2017,27(10):54-59.
 PANG Xiao-shuang,WANG Xing-bo. Sensor Selection Algorithm for Target Tracking with PCRLB[J].,2017,27(10):54-59.
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 基于PCRLB的目标跟踪节点选择算法()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
27
期数:
2017年10期
页码:
54-59
栏目:
智能、算法、系统工程
出版日期:
2017-10-10

文章信息/Info

Title:
 Sensor Selection Algorithm for Target Tracking with PCRLB
文章编号:
1673-629X(2017)10-0054-06
作者:
 庞小双王邢波
 南京邮电大学 自动化学院
Author(s):
 PANG Xiao-shuangWANG Xing-bo
关键词:
 目标跟踪节点选择均方根误差后验-克拉美罗下界扩展H∞滤波无线传感器网络
Keywords:
 target trackingsensor selectionRMSE PCRLBextended H∞ filterwireless sensor network
分类号:
TP301.6
文献标志码:
A
摘要:
 针对能量、带宽、存储等资源限制的无线传感器网络下的目标跟踪问题,提出了基于扩展H∞ 滤波的后验-克拉美罗下界(PCRLB)传感器节点的选择算法.该算法可随时间动态选择一个最优传感器集合并将均方根误差(RMSE)作为优化目标跟踪的性能.无线传感器网络中对于非线性、非高斯的动态系统,采用蒙特卡罗方法计算基于状态估计误差的一步向前Cramer-Rao下界,利用扩展H∞ 滤波器对目标状态和PCRLB进行逼近估计,并以此作为传感器节点选择标准以实现传感器的在线选择.基于Matlab工具箱的计算机仿真结果表明,相对于随机传感器节点选择算法和基于最近邻的传感器节点选择算法,基于后验-克拉美罗下界的目标跟踪传感器观测节点选择算法具有更好的有效性和优越性.
Abstract:
 For target tracking problems limited by resources like energy,bandwidth and storage under wireless sensor networks,a kind of sensor selection algorithm of Posterior Cramer-Rao Lower Bound ( PCRLB) based on the extended H∞ filter is proposed,which can se-lect an optimal sensor set dynamically with time and optimize tracking performance in terms of Root Mean Square Error ( RMSE) . Monte Carlo method is adopted to compute one-step look-ahead CRLB on the state estimation error in a nonlinear,possibly non-Gaussian and dynamic system with extended H∞ filter for approximate estimation of target state and PCRLB which are presented as the sensor selection criterion to realize the sensor options online. Simulation results with Matlab toolbox show that it has owned better effectiveness and superi-ority than stochastic sensor node selection algorithm and sensor node selection algorithm based on nearest neighbor.

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更新日期/Last Update: 2017-11-23