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 language | English |
|---|---|
| Pages (from-to) | 913-931 |
| Number of pages | 19 |
| Journal | International Journal of Systems Science |
| Volume | 21 |
| Issue number | 5 |
| DOIs | |
| Publication status | Published - 1990 |
| Externally published | Yes |
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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 journal › Article
}
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 -