Steady-state error covariances of fixed-point smoothers

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

The estimation error covariance of a fixed-point smoother in the steady-state, which has the steady-state solution of the Kalman filter as the initial condition, is considered for both continuous- and discrete-time systems. Applying some results on a stabilizing solution for a forward-pass fixed-interval smoother, a necessary and sufficient condition is given for assuring the existence of a unique stabilizing solution for such a fixed-point smoother. It is then shown that the resulting condition is equivalent to a well-known condition for the existence of a unique stabilizing solution of the Kalman filter or of the backward information filter.

Original languageEnglish
Pages (from-to)1323-1337
Number of pages15
JournalInternational Journal of Systems Science
Volume18
Issue number7
DOIs
Publication statusPublished - 1987
Externally publishedYes

Fingerprint

Kalman filters
Fixed point
Kalman Filter
Error analysis
Continuous-time Systems
Steady-state Solution
Estimation Error
Discrete-time Systems
Initial conditions
Filter
Necessary Conditions
Interval
Sufficient Conditions
Kalman filter
Estimation error
Discrete-time

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science Applications
  • Theoretical Computer Science
  • Computational Theory and Mathematics
  • Management Science and Operations Research

Cite this

Steady-state error covariances of fixed-point smoothers. / Watanabe, Keigo.

In: International Journal of Systems Science, Vol. 18, No. 7, 1987, p. 1323-1337.

Research output: Contribution to journalArticle

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