Linearly constrained estimation via state space decomposition

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Abstract

This paper considers the estimation problem of the linearly constrained state. By combining the auxiliary dynamics and the constraint, the evolution of the constrained state is depicted via state space decomposition techniques. The effects of the incorporated constraints on the observability of the system model are also discussed. Based on different deterministic sampling methods, two algorithms for the linearly constrained state are presented. Finally, the effectiveness of the two algorithms is measured by a numerical simulation.

Original languageEnglish
Title of host publicationFUSION 2014 - 17th International Conference on Information Fusion
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9788490123553
StatePublished - 3 Oct 2014
Event17th International Conference on Information Fusion, FUSION 2014 - Salamanca, Spain
Duration: 7 Jul 201410 Jul 2014

Publication series

NameFUSION 2014 - 17th International Conference on Information Fusion

Conference

Conference17th International Conference on Information Fusion, FUSION 2014
Country/TerritorySpain
CitySalamanca
Period7/07/1410/07/14

Keywords

  • Linear constraint
  • optimal estimation
  • state estimation
  • system filtering

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