Decentralized estimation algorithms for a backward pass fixed-interval smoother

Keigo Watanabe, Spyros G. Tzafestas

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

Decentralized smoothing algorithms are described for parallel-processing of the multisensor data obtained through linear discrete-time systems. The global fixed-interval smoother of backward-pass in time is used, modified so as to use the U-D factorization. Two cases are considered for the problems of decentralized smoothing and smoothing update: When the local forward-pass information filtered estimates are available, and when the local-smoothed estimates are available. It is then shown that the resulting algorithms are the dual versions of algorithms in a forward-pass realization derived by authors. The situation where the data at each local processor are to be time-sequential is also examined.

Original languageEnglish
Pages (from-to)913-931
Number of pages19
JournalInternational Journal of Systems Science
Volume21
Issue number5
DOIs
Publication statusPublished - 1990
Externally publishedYes

Fingerprint

Estimation Algorithms
Decentralized
Interval
Smoothing
Smoothing Algorithm
Discrete-time Linear Systems
Parallel Processing
Factorization
Estimate
Update
Processing

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science Applications
  • Theoretical Computer Science
  • Computational Theory and Mathematics
  • Engineering(all)

Cite this

Decentralized estimation algorithms for a backward pass fixed-interval smoother. / Watanabe, Keigo; Tzafestas, Spyros G.

In: International Journal of Systems Science, Vol. 21, No. 5, 1990, p. 913-931.

Research output: Contribution to journalArticle

@article{ba871e9ec22a48dcafbc6f70768585d6,
title = "Decentralized estimation algorithms for a backward pass fixed-interval smoother",
abstract = "Decentralized smoothing algorithms are described for parallel-processing of the multisensor data obtained through linear discrete-time systems. The global fixed-interval smoother of backward-pass in time is used, modified so as to use the U-D factorization. Two cases are considered for the problems of decentralized smoothing and smoothing update: When the local forward-pass information filtered estimates are available, and when the local-smoothed estimates are available. It is then shown that the resulting algorithms are the dual versions of algorithms in a forward-pass realization derived by authors. The situation where the data at each local processor are to be time-sequential is also examined.",
author = "Keigo Watanabe and Tzafestas, {Spyros G.}",
year = "1990",
doi = "10.1080/00207729008910421",
language = "English",
volume = "21",
pages = "913--931",
journal = "International Journal of Systems Science",
issn = "0020-7721",
publisher = "Taylor and Francis Ltd.",
number = "5",

}

TY - JOUR

T1 - Decentralized estimation algorithms for a backward pass fixed-interval smoother

AU - Watanabe, Keigo

AU - Tzafestas, Spyros G.

PY - 1990

Y1 - 1990

N2 - Decentralized smoothing algorithms are described for parallel-processing of the multisensor data obtained through linear discrete-time systems. The global fixed-interval smoother of backward-pass in time is used, modified so as to use the U-D factorization. Two cases are considered for the problems of decentralized smoothing and smoothing update: When the local forward-pass information filtered estimates are available, and when the local-smoothed estimates are available. It is then shown that the resulting algorithms are the dual versions of algorithms in a forward-pass realization derived by authors. The situation where the data at each local processor are to be time-sequential is also examined.

AB - Decentralized smoothing algorithms are described for parallel-processing of the multisensor data obtained through linear discrete-time systems. The global fixed-interval smoother of backward-pass in time is used, modified so as to use the U-D factorization. Two cases are considered for the problems of decentralized smoothing and smoothing update: When the local forward-pass information filtered estimates are available, and when the local-smoothed estimates are available. It is then shown that the resulting algorithms are the dual versions of algorithms in a forward-pass realization derived by authors. The situation where the data at each local processor are to be time-sequential is also examined.

UR - http://www.scopus.com/inward/record.url?scp=0025432379&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0025432379&partnerID=8YFLogxK

U2 - 10.1080/00207729008910421

DO - 10.1080/00207729008910421

M3 - Article

AN - SCOPUS:0025432379

VL - 21

SP - 913

EP - 931

JO - International Journal of Systems Science

JF - International Journal of Systems Science

SN - 0020-7721

IS - 5

ER -