Target Tracking Fusion

Target Tracking Fusion is a multisensor data integration framework that combines spatial and temporal observations from multiple sensors to estimate the trajectory and state of a moving object, distinguished by its emphasis on temporal coherence, dynamic motion modeling, and probabilistic association of target identities across heterogeneous sensor inputs.

56

Publications

2.5K

Citations

177

Authors

87

Institutions

Publications per year

2017–2026

17

Variants

Multi-sensor Target Tracking

Authors

177

  1. YB
    Yaakov Bar‐Shalom

    University of Connecticut, United States

    3 publications · 562 citations

    3

    h-index

  2. ZJ
    Zhen Jia

    University of Technology Sydney, Australia

    2 publications · 75 citations

    2

    h-index

  3. EB
    Erik Blasch

    United States Air Force Research Laboratory, United States

    2 publications · 64 citations

    2

    h-index

  4. CC
    Craig Carthel

    NATO Centre for Maritime Research and Experimentation, Italy

    2 publications · 61 citations

    2

    h-index

  5. PW
    Peter Willett

    University of Connecticut, United States

    2 publications · 27 citations

    2

    h-index

1–5 of 177

Venues

  1. 4

    h-index

  2. 4

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  3. International Conference on Information Fusion

    Conference · 3 publications · 99 citations

    3

    h-index

  4. 2

    h-index

  5. Science China Information Sciences

    2 publications · 48 citations

    2

    h-index

1–5