Kalman Smoother

A Kalman Smoother is an optimal recursive estimation algorithm that belongs to the class of Bayesian filtering methods, distinguished from its sibling filters by computing the maximum a posteriori estimate of the state sequence in a forward-backward manner, incorporating all available measurements across time rather than only those up to the current time step.

391

Publications

20.9K

Citations

939

Authors

450

Institutions

Publications per year

2017–2026

88

Authors

939

  1. MB
    Marc Bocquet

    Centre d'Enseignement et de Recherche en Environnement Atmosphérique, France

    9 publications · 484 citations

    9

    h-index

  2. GE
    Geir Evensen

    Nansen Environmental and Remote Sensing Center

    8 publications · 1.1K citations

    8

    h-index

  3. PA
    Pasi A. Karjalainen

    University of Eastern Finland, Finland

    8 publications · 327 citations

    8

    h-index

  4. MI
    Mahdi Imani

    Texas A&M University, United States

    7 publications · 340 citations

    7

    h-index

  5. UB
    Ulisses Braga-Neto

    Texas A&M University, United States

    6 publications · 328 citations

    6

    h-index

1–5 of 939

Venues

  1. IEEE Transactions on Signal Processing

    17 publications · 791 citations

    14

    h-index

  2. IEEE Transactions on Automatic Control

    11 publications · 518 citations

    11

    h-index

  3. 11

    h-index

  4. Tellus A Dynamic Meteorology and Oceanography

    11 publications · 526 citations

    10

    h-index

  5. Monthly Weather Review

    9 publications · 979 citations

    9

    h-index

1–5