A Global Optimal Association Algorithm Based on Fuzzy Comprehensive Decision-Making

In this study, a global optimal association algorithm based on fuzzy comprehensive decision-making is proposed to enhance the accuracy and computational efficiency of associating radar and Automatic Identification System (AIS) track data. The algorithm combines spatial partitioning to reduce computa...

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Bibliographic Details
Published in2023 IEEE 6th International Conference on Electronic Information and Communication Technology (ICEICT) pp. 1135 - 1139
Main Authors Tian, Lu, Tan, Shizhe, Chen, Wei, Cao, Zhike, Xing, Xiangdong, Wang, Lizhi, Gong, Runze
Format Conference Proceeding
LanguageEnglish
Published IEEE 21.07.2023
Subjects
AIS
Calibration
Decision making
error calibration
global optimal association
Partitioning algorithms
Radar
Radar tracking
Runtime
spatial partitioning
Surveillance
track data association
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Summary:In this study, a global optimal association algorithm based on fuzzy comprehensive decision-making is proposed to enhance the accuracy and computational efficiency of associating radar and Automatic Identification System (AIS) track data. The algorithm combines spatial partitioning to reduce computational complexity, and utilizes error calibration and global optimal methods to enhance association accuracy. The experimental results show that the proposed algorithm achieves higher association accuracy and shorter running time compared to traditional track association algorithms. This improvement is particularly notable when handling a large number of tracks.
ISSN:2836-7782
DOI:10.1109/ICEICT57916.2023.10245612