Event-Based Recursive Distributed Filtering

  • Qinyuan Liu
  • Zidong Wang
  • Xiao He
Part of the Studies in Systems, Decision and Control book series (SSDC, volume 178)


An important practical problem with the wireless sensor networks is how to find distributed estimators or filters to extract the information about the state vectors of the target plants from observations contaminated with external disturbances. It is generally known that the traditional Kalman filter algorithm is a recursive least mean square (LMS) one dealing with a single node and is optimal for linear systems with exact system models. On the other hand, to make use of the spatial information of the sensor nodes, distributed filtering problems have recently gained much research attention.


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© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Department of Computer Science and TechnologyTongji UniversityShanghaiChina
  2. 2.Department of Computer ScienceBrunel University LondonUxbridgeUK
  3. 3.Department of AutomationTsinghua UniversityBeijingChina

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