Multiple Hypothesis Tracking

Multiple Hypothesis Tracking is a data association method that maintains multiple probabilistic hypotheses over time to resolve ambiguities in tracking multiple targets in cluttered environments, distinguishing it from single-hypothesis approaches by its explicit representation of track uncertainty through competing, persistent trajectories.

339

Publications

21K

Citations

697

Authors

291

Institutions

Publications per year

2017–2026

51

Authors

697

  1. PW
    Peter Willett

    University of Connecticut, United States

    21 publications · 625 citations

    15

    h-index

  2. YB
    Yaakov Bar‐Shalom

    University of Connecticut, United States

    16 publications · 628 citations

    14

    h-index

  3. WK
    Wolfgang Koch

    Fraunhofer Institute for Communication, Information Processing and Ergonomics, Germany

    12 publications · 557 citations

    11

    h-index

  4. CC
    Craig Carthel

    NATO Centre for Maritime Research and Experimentation, Italy

    9 publications · 211 citations

    10

    h-index

  5. SC
    Stefano Coraluppi

    NATO Centre for Maritime Research and Experimentation, Italy

    10 publications · 242 citations

    10

    h-index

1–5 of 697

Venues

  1. 28

    h-index

  2. 15

    h-index

  3. IEEE Transactions on Signal Processing

    7 publications · 921 citations

    8

    h-index

  4. arXiv (Cornell University)

    Repository · 6 publications · 97 citations

    6

    h-index

  5. International Conference on Information Fusion

    Conference · 6 publications · 98 citations

    6

    h-index

1–5