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A Self-Tuning Filter for Fixed-Lag Smoothing

Hagander, Per LU and Wittenmark, Björn LU (1977) In IEEE Transactions on Information Theory 23(3). p.377-384
Abstract
The problem of estimating a discrete-time stochastic signal which is corrupted by additive white measurement noise is discussed. How the stationary solution to the fixed-lag smoothing problem can be obtained is shown. The first step is to construct an innovation model for the process. It is then shown how the fixed-lag smoother can be determined from the polynomials in the transfer function of the innovation model. In many applications, the signal model and the characteristics of the noise process are unknown. It is shown that it is possible to derive an algorithm which on-line finds the optimal fixed-lag smoother, a self-tuning smoother. The self-tuning smoother consists of two parts: an on-line estimation of the parameters in the... (More)
The problem of estimating a discrete-time stochastic signal which is corrupted by additive white measurement noise is discussed. How the stationary solution to the fixed-lag smoothing problem can be obtained is shown. The first step is to construct an innovation model for the process. It is then shown how the fixed-lag smoother can be determined from the polynomials in the transfer function of the innovation model. In many applications, the signal model and the characteristics of the noise process are unknown. It is shown that it is possible to derive an algorithm which on-line finds the optimal fixed-lag smoother, a self-tuning smoother. The self-tuning smoother consists of two parts: an on-line estimation of the parameters in the one-step ahead predictor of the measured signal, and a computation of the smoother coefficients by simple manipulation of the predictor parameters. The smoother has good transient, as well as good asymptotic, properties. (Less)
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Contribution to journal
publication status
published
subject
in
IEEE Transactions on Information Theory
volume
23
issue
3
pages
377 - 384
publisher
IEEE--Institute of Electrical and Electronics Engineers Inc.
external identifiers
  • Scopus:0017492697
ISSN
0018-9448
DOI
10.1109/TIT.1977.1055719
language
English
LU publication?
yes
id
53fdc2ed-b07c-4a1d-8983-af7e36f0b132 (old id 4820832)
date added to LUP
2014-12-05 09:34:49
date last changed
2016-08-03 10:02:17
@misc{53fdc2ed-b07c-4a1d-8983-af7e36f0b132,
  abstract     = {The problem of estimating a discrete-time stochastic signal which is corrupted by additive white measurement noise is discussed. How the stationary solution to the fixed-lag smoothing problem can be obtained is shown. The first step is to construct an innovation model for the process. It is then shown how the fixed-lag smoother can be determined from the polynomials in the transfer function of the innovation model. In many applications, the signal model and the characteristics of the noise process are unknown. It is shown that it is possible to derive an algorithm which on-line finds the optimal fixed-lag smoother, a self-tuning smoother. The self-tuning smoother consists of two parts: an on-line estimation of the parameters in the one-step ahead predictor of the measured signal, and a computation of the smoother coefficients by simple manipulation of the predictor parameters. The smoother has good transient, as well as good asymptotic, properties.},
  author       = {Hagander, Per and Wittenmark, Björn},
  issn         = {0018-9448},
  language     = {eng},
  number       = {3},
  pages        = {377--384},
  publisher    = {ARRAY(0x87ea9b0)},
  series       = {IEEE Transactions on Information Theory},
  title        = {A Self-Tuning Filter for Fixed-Lag Smoothing},
  url          = {http://dx.doi.org/10.1109/TIT.1977.1055719},
  volume       = {23},
  year         = {1977},
}