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兵工学报 ›› 2018, Vol. 39 ›› Issue (4): 625-634.doi: 10.3969/j.issn.1000-1093.2018.04.001

• 论文 • 上一篇    下一篇

不完全量测下事件触发卡尔曼一致滤波及在光电探测网中的应用

陈烨, 盛安冬, 戚国庆, 李银伢   

  1. (南京理工大学 自动化学院, 江苏 南京 210094)
  • 收稿日期:2017-06-19 修回日期:2017-06-19 上线日期:2018-05-30
  • 通讯作者: 盛安冬(1964—),男,研究员,博士生导师 E-mail:shengandong@njust.edu.cn
  • 作者简介:陈烨(1989—),男,博士研究生。E-mail:0711370107@163.com
  • 基金资助:
    国家自然科学基金项目(61273076)

Event-triggered Kalman Consensus Filter with Intermittent Measurements and Its Application to the Electro-optical Sensor Network

CHEN Ye, SHENG An-dong, QI Guo-qing, LI Yin-ya   

  1. (School of Automation, Nanjing University of Science and Technology, Nanjing 210094, Jiangsu, China)
  • Received:2017-06-19 Revised:2017-06-19 Online:2018-05-30

摘要: 针对分布式状态估计中卡尔曼一致滤波算法各节点间通信量过大的问题,在保证卡尔曼一致滤波算法估计精度及各节点估计值一致性前提下,为减少各节点间的通信量,提出一种事件触发机制协调各节点间的信息交互过程。推导了相应的卡尔曼一致滤波算法,并证明了其估计误差的有界性;仿真了所提算法在不完全量测下光电探测网中的应用。研究结果表明:与经典卡尔曼一致滤波算法相比,所提算法可在节约网络通信资源前提下,保证网络中各节点估计精度及估计值的一致性。

关键词: 光电探测网, 分布式估计算法, 不完全量测, 事件触发, 卡尔曼一致滤波

Abstract: This paper focuses on the problem of the too much communication amount of the Kalman consensus filtering (KCF) algorithm in the distributed state estimation. An event-triggered mechanism is proposed to decrease the communication amount among nodes, meanwhile ensuring the estimation accuracy and the consensus of estimated values of each node. The corresponding estimation algorithm is derived. The boundedness of estimated error of the proposed algorithm is also proven. The proposed algorithm is tested in an electro-optical sensor network with intermittent measurements. The result shows that, compared with the classical Kalman consensus filtering algorithm, the proposed algorithm can save the network’s communication resources and ensure the estimation accuracy of each node in the network. Key

Key words: electro-opticalsensornetwork, distributedestimationalgorithm, intermittentmeasurement, event-triggeredmechanism, Kalmanconsensusfilter

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