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分簇传感网络系统两级鲁棒观测融合Kalman滤波器

张鹏 齐文娟 邓自立

张鹏, 齐文娟, 邓自立. 分簇传感网络系统两级鲁棒观测融合Kalman滤波器. 自动化学报, 2014, 40(11): 2585-2594. doi: 10.3724/SP.J.1004.2014.02585
引用本文: 张鹏, 齐文娟, 邓自立. 分簇传感网络系统两级鲁棒观测融合Kalman滤波器. 自动化学报, 2014, 40(11): 2585-2594. doi: 10.3724/SP.J.1004.2014.02585
ZHANG Peng, QI Wen-Juan, DENG Zi-Li. Two-level Robust Measurement Fusion Kalman Filter for Clustering Sensor Networks. ACTA AUTOMATICA SINICA, 2014, 40(11): 2585-2594. doi: 10.3724/SP.J.1004.2014.02585
Citation: ZHANG Peng, QI Wen-Juan, DENG Zi-Li. Two-level Robust Measurement Fusion Kalman Filter for Clustering Sensor Networks. ACTA AUTOMATICA SINICA, 2014, 40(11): 2585-2594. doi: 10.3724/SP.J.1004.2014.02585

分簇传感网络系统两级鲁棒观测融合Kalman滤波器

doi: 10.3724/SP.J.1004.2014.02585
基金项目: 

Supported by National Natural Science Foundation of China (60874063), and Innovation and Scientific Research Foundation of Graduate Student of Heilongjiang Province (YJSCX2012-263HLJ)

Two-level Robust Measurement Fusion Kalman Filter for Clustering Sensor Networks

Funds: 

Supported by National Natural Science Foundation of China (60874063), and Innovation and Scientific Research Foundation of Graduate Student of Heilongjiang Province (YJSCX2012-263HLJ)

  • 摘要: 研究了分簇传感网络分布式融合Kalman滤波器.根据最邻近原则将传感网络分成簇,每簇由传感节点和簇首组成.应用极大极小鲁棒估计原理,基于带噪声方差最大保守上界的最坏保守系统,对带不确定性噪声方差的分簇传感网络系统提出了两级鲁棒观测融合Kalman滤波器.当传感器数量非常多的时候它可以明显减小通信负担.在鲁棒性分析中利用Lyapunov方程方法证明了局部和融合Kalman滤波器的鲁棒性.提出了鲁棒精度的概念,并证明了局部和融合鲁棒Kalman滤波器之间的鲁棒精度关系.证明了两级加权观测融合器的鲁棒精度等价于相应的全局集中式鲁棒融合器的鲁棒精度,并且高于每个局部观测融合器的鲁棒精度.一个仿真例子说明上述结果的准确性.
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出版历程
  • 收稿日期:  2013-06-14
  • 修回日期:  2014-01-20
  • 刊出日期:  2014-11-20

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