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一种适用于稀疏无线传感器网络的改进分布式UIF算法

汤文俊 张国良 曾静 孙一杰 吴晋

汤文俊, 张国良, 曾静, 孙一杰, 吴晋. 一种适用于稀疏无线传感器网络的改进分布式UIF算法. 自动化学报, 2014, 40(11): 2490-2498. doi: 10.3724/SP.J.1004.2014.02490
引用本文: 汤文俊, 张国良, 曾静, 孙一杰, 吴晋. 一种适用于稀疏无线传感器网络的改进分布式UIF算法. 自动化学报, 2014, 40(11): 2490-2498. doi: 10.3724/SP.J.1004.2014.02490
TANG Wen-Jun, ZHANG Guo-Liang, ZENG Jing, SUN Yi-Jie, WU Jin. An Improved Distributed Unscented Information Filter Algorithm for Sparse Wireless Sensor Networks. ACTA AUTOMATICA SINICA, 2014, 40(11): 2490-2498. doi: 10.3724/SP.J.1004.2014.02490
Citation: TANG Wen-Jun, ZHANG Guo-Liang, ZENG Jing, SUN Yi-Jie, WU Jin. An Improved Distributed Unscented Information Filter Algorithm for Sparse Wireless Sensor Networks. ACTA AUTOMATICA SINICA, 2014, 40(11): 2490-2498. doi: 10.3724/SP.J.1004.2014.02490

一种适用于稀疏无线传感器网络的改进分布式UIF算法

doi: 10.3724/SP.J.1004.2014.02490
基金项目: 

陕西省基金项目 (2012K06-45)资助

详细信息
    作者简介:

    张国良 第二炮兵工程大学教授, 博士.主要研究方向为机器人技术, 先进控制理论与应用. E-mail: zhgl@sohu.com

    通讯作者:

    汤文俊, 第二炮兵工程大学博士研究生.主要研究方向为多智能体协同导航与控制, 无线传感器网络信息融合. 本文通信作者. E-mail: 13468972665@163.com

An Improved Distributed Unscented Information Filter Algorithm for Sparse Wireless Sensor Networks

Funds: 

Supported by Fund Program of Shaanxi Province (2012K06-45)

  • 摘要: 分布式无迹信息滤波(Distributed unscented information filter,DUIF)算法是一种有效的非线性分布式状态估计多源信息融合方法,然而当将该算法应用于稀疏无线传感器网络(Wireless sensor networks,WSN)时,稀疏WSN中存在的无效节点会引起使滤波趋于发散的平均一致误差.针对该问题,本文提出一种改进DUIF算法.该算法不改变DUIF算法的级联结构,而是将其底层和上层滤波器分别改进为局部无迹信息滤波器(Local unscented information filter,LUIF)和加权平均一致性滤波器.LUIF对每个节点的局部多源观测信息进行局部融合,得到局部的后验估计信息向量和矩阵,进而将它们作为加权平均一致性滤波器的输入,最终得到不包含平均一致误差的分布式后验估计结果.其中,加权平均一致性滤波器是通过对由LUIF输出的局部后验估 计信息向量和矩阵分别进行平均一致性滤波而得以在改进DUIF算法框架下实现的.同时,在此过程中,相邻节点之间的状态估计互相关信息也被引入改进DUIF算法的输出结果中,进一步增强了滤波的可靠性.仿真实验结果表明,改进DUIF算法能够在稀疏WSN中对机动目标进行有效跟踪,在估计精度和抑制滤波发散方面明显优于标准DUIF算法.
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出版历程
  • 收稿日期:  2013-09-26
  • 修回日期:  2014-06-30
  • 刊出日期:  2014-11-20

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