On sequential Kalman filtering with scheduled measurements

Gang Wang, Jie Chen, Jian Sun

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Scopus citations

Abstract

The stability problem of Kalman filtering for linear stochastic systems with scheduled measurements in [1] is reconsidered in this paper. The transmission of a vector observation from the sensor to the remote estimator is realized by sequentially transmitting each component of the observation to the estimator in one time step. The communication of each component is triggered if and only if the corresponding component of normalized measurement innovation vector is larger than a given threshold. As a complementary to [1], we extend the measurement data scheduler to have different thresholds assigned to different components of the normalized measurement innovation vector and similarly derive the sequential Kalman filter. Moreover, the sufficient and necessary conditions for guaranteeing the stability of mean squared estimation error are established for general linear systems by explicitly investigating the convergence properties of a specially constructed axillary function.

Original languageEnglish (US)
Title of host publication2013 IEEE International Conference on Cyber Technology in Automation, Control and Intelligent Systems, IEEE-CYBER 2013
Pages450-455
Number of pages6
DOIs
StatePublished - Dec 1 2013
Event3rd Annual IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems, IEEE-CYBER 2013 - Nanjing, China
Duration: May 26 2013May 29 2013

Publication series

Name2013 IEEE International Conference on Cyber Technology in Automation, Control and Intelligent Systems, IEEE-CYBER 2013

Other

Other3rd Annual IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems, IEEE-CYBER 2013
CountryChina
CityNanjing
Period5/26/135/29/13

Keywords

  • Sequential Kalman filtering
  • linear stochastic systems
  • scheduled measurements
  • stability
  • wireless sensor networks

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