Fixed-interval Smoothing

Fixed-Interval Smoothing is a Bayesian filtering method that estimates the posterior distribution of a system's state over a complete time interval using all available observations within that interval, distinguishing it from filtering and prediction by incorporating future measurements to refine past state estimates.

110

Publications

4.6K

Citations

227

Authors

151

Institutions

Publications per year

2017–2026

15

Authors

227

  1. RJ
    Robert J. Elliott

    University of Calgary, Canada

    4 publications · 108 citations

    4

    h-index

  2. KW
    Keigo Watanabe

    Saga University, Japan

    4 publications · 62 citations

    4

    h-index

  3. SG
    Spyros G. Tzafestaş

    National Technical University of Athens, Greece

    3 publications · 87 citations

    3

    h-index

  4. SN
    Seiichi Nakamori

    Kagoshima University, Japan

    3 publications · 32 citations

    3

    h-index

  5. WM
    W.P. Malcolm

    The University of Adelaide, Australia

    3 publications · 75 citations

    3

    h-index

1–5 of 227

Venues

  1. IEEE Transactions on Automatic Control

    17 publications · 819 citations

    15

    h-index

  2. IEEE Transactions on Signal Processing

    12 publications · 504 citations

    12

    h-index

  3. International Journal of Control

    7 publications · 169 citations

    7

    h-index

  4. Journal of Guidance Control and Dynamics

    4 publications · 159 citations

    4

    h-index

  5. 4

    h-index

1–5