| 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 2596 全文点击 1698 投稿时间：2010-02-22 修订日期：2011-08-24 |
| 查看全文 查看/发表评论 下载PDF阅读器 |
| 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). |
|
| 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. |