Process Noise Estimation

Process Noise Estimation is a methodological framework within the broader class of state estimation techniques that specifically characterizes and quantifies the uncertainty arising from unmodeled dynamics or disturbances in the system evolution model used in Kalman filtering.

345

Publications

16.6K

Citations

859

Authors

388

Institutions

Publications per year

2017–2026

101

Authors

859

  1. YB
    Yaakov Bar‐Shalom

    University of Connecticut, United States

    8 publications · 716 citations

    8

    h-index

  2. WB
    W.D. Blair

    Naval Surface Warfare Center, United States

    7 publications · 145 citations

    7

    h-index

  3. JL
    John L. Crassidis

    University at Buffalo, State University of New York, United States

    4 publications · 84 citations

    4

    h-index

  4. PT
    P.C. Thijssen

    University of Amsterdam, Netherlands

    4 publications · 125 citations

    4

    h-index

  5. KC
    Kuo‐Chu Chang

    George Mason University, United States

    3 publications · 392 citations

    3

    h-index

1–5 of 859

Venues

  1. IEEE Transactions on Automatic Control

    20 publications · 2.1K citations

    17

    h-index

  2. 10

    h-index

  3. IEEE Access

    9 publications · 478 citations

    10

    h-index

  4. Journal of Guidance Control and Dynamics

    8 publications · 292 citations

    8

    h-index

  5. 6

    h-index

1–5