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New design of linear least-squares fixed-interval smoother using covariance information

✍ Scribed by Seiichi Nakamori; Akira Hataji

Publisher: Elsevier Science
Year: 1981
Tongue: English
Weight: 256 KB
Volume: 17
Category: Article
ISSN: 0005-1098
DOI: 10.1016/0005-1098(81)90042-x

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✦ Synopsis

This paper derives recursive linear least-squares fixed-interval smoothing algorithm using covariance information by applying an invariant imbedding method to a Wiener-Hopf integral equation. The algorithm is obtained for the white plus coloured observation noise. The signal process is nonstationary stochastic. Autocovariance functions of the signal and the coloured noise are expressed using a degenerate kernel. The degenerate kernel can represent general covariance functions of nonstationary stochastic processes by a finite sum of nonrandom functions.

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