What is the covariance analog of the Paige and Saunders information filter

Michael R. Osborne, T PRVAN

Research output: Contribution to journalArticle

Abstract

In this paper a square root covariance form of the Kalman filter is presented which is in many ways the covariance analog of the Paige and Saunders information filter [SIAM J. Numer. Anal., 14 (1977), pp. 180-193] and possesses many of the advantages of their algorithm. For example, it is a true square root implementation; but the distinctive feature which it shares with the Paige and Saunders algorithm is a compact, convenient, and effective square root implementation of the interpolation smoother. The algorithm is based on the Duncan and Horne generalised least squares form of the filter equations [J. Amer. Statist. Assoc., 67 (1972), pp. 816-821], but uses these in a recursive manner.

Original languageEnglish
Pages (from-to)1324-1331
Number of pages8
JournalSiam journal on scientific and statistical computing
Volume12
Issue number6
Publication statusPublished - Nov 1991
Externally publishedYes

Keywords

  • KALMAN FILTER
  • COVARIANCE FILTER
  • INFORMATION FILTER
  • SQUARE ROOT FILTER
  • GENERALIZED LEAST SQUARES
  • SMOOTHING STEP
  • DISCRETE

Cite this