引用本文:陈军勇,邬依林,祁恬.无线传感器网络分布式量化卡尔曼滤波[J].控制理论与应用,2011,28(12):1729~1739.[点击复制]
CHEN Jun-yong,WU Yi-lin,QI Tian.Distributed quantized Kalman filtering for wireless sensor networks[J].Control Theory and Technology,2011,28(12):1729~1739.[点击复制]
无线传感器网络分布式量化卡尔曼滤波
Distributed quantized Kalman filtering for wireless sensor networks
摘要点击 2840  全文点击 2459  投稿时间:2010-12-11  修订日期:2011-07-05
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DOI编号  10.7641/j.issn.1000-8152.2011.12.CCTA101425
  2011,28(12):1729-1739
中文关键词  无线传感器网络  分布式量化卡尔曼滤波  动态Lloyd-Max量化器  稳定性
英文关键词  wireless sensor networks  distributed quantized Kalman filtering  dynamic Lloyd-Max quantizer  stability
基金项目  国家自然科学基金重点资助项目(60834003); 国家自然科学基金资助项目(60774057); 国家科技部“973”计划资助项目(2010CB731802).
作者单位E-mail
陈军勇 华南理工大学 自动化科学与工程学院 chenjunyong102@gmail.com 
邬依林 华南理工大学 自动化科学与工程学院
广东第二师范学院 计算机科学系 
 
祁恬* 华南理工大学 自动化科学与工程学院 auqt@scut.edu.cn 
中文摘要
      本文针对无线传感器网络中的目标跟踪问题, 研究了分布式量化卡尔曼滤波问题. 由于网络中存在能量和带宽限制, 传感器传输的数据必须经过量化处理. 考虑一个线性离散随机动态系统, 首先提出了一种动态Lloyd-Max量化器并设计了其在线更新方案, 然后基于贝叶斯原理导出了递归形式的最优量化卡尔曼滤波器, 同时给出了一种渐近等价的迭代算法, 并进一步分析了量化卡尔曼滤波器的稳定性. 最后, 仿真结果验证了所设计算法的可行性与有效性.
英文摘要
      We study the distributed quantized Kalman filtering for the target-tracking in wireless sensor networks (WSNs). Because of the constraints on power and bandwidth in WSNs, sensor data have to be quantized before transmission. A linear discrete-time stochastic dynamic system is employed for this purpose. First, a dynamic Lloyd-Max quantizer is adopted and the corresponding online update scheme is designed. Then, the optimal recursive quantized Kalman filter is derived based on the Bayesian principles, and an asymptotically equivalent iterative algorithm is developed. The stability of the quantized Kalman filter is analyzed. Simulation results show the feasibility and effectiveness of the designed algorithms.