Open AccessA Multi-objective Tracking Task Assignment Algorithm Based on Game Theory
Author(s) -
Bei Quan,
Xiaohong Lü,
Yumeng Zhang,
Zhiying Mou
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1802/3/032115
Subject(s) - tracking (education) , task (project management) , game theory , computer science , tracking error , function (biology) , mathematical optimization , payment , artificial intelligence , algorithm , mathematics , engineering , control (management) , mathematical economics , psychology , pedagogy , systems engineering , evolutionary biology , biology , world wide web
Aiming at the relationship between competition and cooperation among sensors in multi-target tracking task allocation, this paper proposes a game theory-based method to allocate sensor resources for multi-target tracking tasks. The dissertation first establishes a target tracking model and designs a game theory payment function based on the model. Then a multi-sensor multi-target tracking task allocation game model is designed. Finally, a multi-target tracking task allocation algorithm based on game theory is given. Compared with other allocation algorithms, the average tracking error of the proposed allocation algorithm is reduced from 68.5630m to 19.7601m through experiments.