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Decoupling of Filtering Equations

  • Charles K. Chui
  • Guanrong Chen
Part of the Springer Series in Information Sciences book series (SSINF, volume 17)

Abstract

The limiting (or steady-state) Kalman filter provides a very efficient method for estimating the state vector in a time-invariant linear system in real-time. However, if the state vector has a very high dimension n, and only a few components are of interest, this filter gives an abundance of useless information, an elimination of which should improve the efficiency of the filtering process. A decoupling method is introduced in this chapter for this purpose. It allows us to decompose an n-dimensional limiting kalman filtering algorithm into n independent one-dimensional recursive so that we may drop the ones that are of little interest.

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Copyright information

© Springer-Verlag Berlin Heidelberg 1991

Authors and Affiliations

  • Charles K. Chui
    • 1
  • Guanrong Chen
    • 2
  1. 1.Department of Mathematics and Department of Electrical EngineeringTexas A&M UniversityCollege StationUSA
  2. 2.Department of Electrical EngineeringUniversity of HoustonHoustonUSA

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