Kalman Filter-based Localization

Kalman Filter-Based Localization is a state estimation method that employs the Kalman filter to recursively predict and update the position and velocity of a dynamic system by minimizing the mean squared error in the presence of noisy sensor measurements.

577

Publications

24.5K

Citations

1.6K

Authors

574

Institutions

Publications per year

2017–2026

196

Authors

1.6K

  1. SI
    Stergios I. Roumeliotis

    University of Minnesota, United States

    10 publications · 837 citations

    10

    h-index

  2. LC
    Long Cheng

    Northeastern University, China

    8 publications · 143 citations

    8

    h-index

  3. HD
    Hugh Durrant‐Whyte

    The University of Sydney, Australia

    7 publications · 189 citations

    7

    h-index

  4. YX
    Yuan Xu

    University of Jinan, China

    6 publications · 279 citations

    6

    h-index

  5. HH
    Huosheng Hu

    University of Essex, United Kingdom

    5 publications · 154 citations

    5

    h-index

1–5 of 1.6K

Venues

  1. Sensors

    30 publications · 689 citations

    19

    h-index

  2. IEEE Access

    18 publications · 797 citations

    15

    h-index

  3. 12

    h-index

  4. 8

    h-index

  5. IEEE Sensors Journal

    8 publications · 562 citations

    8

    h-index

1–5