A new forward-pass fixed-interval smoother using the U-D information matrix factorization

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14 Citations (Scopus)

Abstract

A new U-D factorized smoothing algorithm that is numerically stable and reliable is developed by using a forward-pass fixed-interval smoother recursion. Introducing a gain for a backward-pass information filter and the notion of an input to the smoother and decomposing the system noises into each element, it is shown that three famous U-D algorithms can be naturally applied to construct such a smoother. The new result does not necessitate two burdensome matrix inversions, or any algebraic computations equivalent to them, for the transition matrix and the predicted error covariance, which are at present necessary for the Bierman's U-D smoother. Consequently, compared with the result of Bierman, the present algorithm can deal with a broader system, which may cover a time-delay system, and provide an improvement in computation speed and computer storage.

Original languageEnglish
Pages (from-to)465-475
Number of pages11
JournalAutomatica
Volume22
Issue number4
DOIs
Publication statusPublished - Jul 1986
Externally publishedYes

Keywords

  • Kalman filters
  • Smoothing
  • aerospace trajectories
  • computational methods
  • numerical methods
  • optimal filtering

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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