Research Progress in Multi-Sensor Data Fusion Algorithms

With the rapid advancement of modern science and technology, the importance of multi-sensor data fusion technology in various applications has become increasingly prominent. However, traditional non-intelligent fusion methods reveal many shortcomings when dealing with complex and dynamic environments. These methods rely on preset models and algorithms, showing poor adaptability to system nonlinearities, time-varying characteristics, and uncertainties, making it challenging to achieve real-time, efficient, and accurate information fusion. Moreover, traditional methods often struggle with processing multi-source heterogeneous data, being easily affected by noise and interference, thus reducing fusion accuracy and system robustness.

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Publication Details

Published
2024-09-13
DOI
https://doi.org/10.1145/3703187.3703279
Primary Topic
Advanced Computational Techniques and Applications
Type
article
Field-Weighted Citation Impact
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article

Research Progress in Multi-Sensor Data Fusion Algorithms

H. Jiang, Hao-Wen Ke
Advanced Computational Techniques and Applications
article

Research Progress in Multi-Sensor Data Fusion Algorithms

H. Jiang, Hao-Wen Ke
article en

Abstract

With the rapid advancement of modern science and technology, the importance of multi-sensor data fusion technology in various applications has become increasingly prominent. However, traditional non-intelligent fusion methods reveal many shortcomings when dealing with complex and dynamic environments. These methods rely on preset models and algorithms, showing poor adaptability to system nonlinearities, time-varying characteristics, and uncertainties, making it challenging to achieve real-time, efficient, and accurate information fusion. Moreover, traditional methods often struggle with processing multi-source heterogeneous data, being easily affected by noise and interference, thus reducing fusion accuracy and system robustness.

Openalex Percentile: Top 78%
Advanced Computational Techniques and Applications
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Research Progress in Multi-Sensor Data Fusion Algorithms — H. Jiang, Hao-Wen Ke · (2024) | TGRS Research Map | TGRS