Sensor Fusion

Sensor fusion is a computational technique that combines data from multiple heterogeneous sensors to produce an integrated environmental state estimate with greater accuracy, completeness, and robustness than any individual sensor could provide independently.

52.3K

Publications

2.8M

Citations

116.7K

Authors

9.6K

Institutions

Publications per year

2017–2026

24K

Authors

116.7K

  1. YB
    Yaakov Bar‐Shalom

    University of Connecticut, United States

    171 publications · 14K citations

    57

    h-index

  2. JC
    Jocelyn Chanussot

    Institut polytechnique de Grenoble, France

    90 publications · 13.3K citations

    50

    h-index

  3. PK
    Pramod K. Varshney

    Syracuse University, United States

    148 publications · 9.6K citations

    49

    h-index

  4. EB
    Erik Blasch

    United States Air Force Research Laboratory, United States

    141 publications · 6.8K citations

    48

    h-index

  5. LZ
    Liangpei Zhang

    Wuhan University, China

    73 publications · 6.4K citations

    43

    h-index

1–5 of 116.7K

Venues

  1. IEEE Transactions on Geoscience and Remote Sensing

    1.1K publications · 88.9K citations

    136

    h-index

  2. Information Fusion

    576 publications · 68.7K citations

    125

    h-index

  3. 122

    h-index

  4. IEEE Transactions on Signal Processing

    723 publications · 58.8K citations

    120

    h-index

  5. Sensors

    2.1K publications · 90.1K citations

    110

    h-index

1–5

See also

Sensor Fusion

Core Methods

Applications

Architectures

Evaluation

Limitations