引用本文:周彦,李建勋,王冬丽.传感器网络中鲁棒状态信息融合抗差卡尔曼滤波器[J].控制理论与应用,2012,29(3):291~297.[点击复制]
ZHOU Yan,LI Jian-xun,WANG Dong-li.Anti-outlier Kalman filter-based robust estimation fusion in wireless sensor networks[J].Control Theory and Technology,2012,29(3):291~297.[点击复制]
传感器网络中鲁棒状态信息融合抗差卡尔曼滤波器
Anti-outlier Kalman filter-based robust estimation fusion in wireless sensor networks
摘要点击 2319  全文点击 1580  投稿时间:2010-02-22  修订日期:2011-08-24
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DOI编号  10.7641/j.issn.1000-8152.2012.3.CCTA100165
  2012,29(3):291-297
中文关键词  无线传感器网络  野值  卡尔曼滤波  融合估计  相关性
英文关键词  wireless sensor network  outlier  Kalman filter  estimation fusion  correlation
基金项目  国家自然科学基金资助项目(60874104, 60935001, 61104210); 上海市重点基础研究资助项目(08JC1411800); 航空科学基金项目(20105557007).
作者单位E-mail
周彦* 湘潭大学 信息工程学院
上海交通大学 自动化系 
sgirld@163.com 
李建勋 上海交通大学 自动化系  
王冬丽 湘潭大学 信息工程学院  
中文摘要
      研究了无线传感器网络中的分布式鲁棒状态信息融合问题. 在局部状态估计层, 基于鲁棒统计学理论提出了适用于噪声相关情况的抗差(扩展)卡尔曼滤波器. 在融合中心层, 针对局部估计相关未知性和不完整性, 给出了不依赖于互协方差阵的稳健航迹融合方法—–内椭球逼近法. 仿真结果证实了算法的有效性: 所提出的抗差卡尔曼滤波器在野值存在情况下, 性能退化远低于传统卡尔曼滤波器(28.6%比428.6%); 所提出的内椭球逼近法获得比协方并交叉法更好的融合估计性能, 且不需要局部估计相关性的先验知识.
英文摘要
      The problem of distributed robust estimation fusion is considered for a hierarchical wireless sensor network (WSN). Based on the theory of robust statistics (RS), a novel anti-outlier (extended) Kalman filter (KF) is presented for local state estimation in a clustered WSN with correlated measuring noises. In the fusion center (FC), a cross-covarianceindependent track fusion approach –- internal ellipsoidal approximation fusion (IEAF) is developed to fuse the local estimates, among which the correlations are usually unknown or incomplete. Simulation results illustrate the significance of the proposed approaches: the presented anti-outlier KF deteriorates in performances much less than the traditional KF (28.6% VS. 428.6%) in the presence of outlier; the proposed IEAF has higher fusion accuracy than the fusion estimator of covariance intersection (CI), and doesn’t need any prior knowledge.