In response to the target state fusion estimation problem during the cooperative target tracking task executed by multiple unmanned aerial vehicles (Multi-UAV), a federated interactive multiple model (FIMM) filtering algorithm is proposed. Firstly, the essential models are established, including the target motion model set, UAV sensor observation model, distributed target state fusion estimation framework, and multi-UAV communication network structure. Secondly, a FIMM filtering algorithm is proposed, where each UAV runs a local interactive multiple model (IMM) filter, and one of the UAVs is selected as the fusion center to fuse local filtering results and output global filtering results. The global filtering information is then distributed among the local filters. Finally, numerical simulations are conducted to confirm the effectiveness of the FIMM algorithm. The numerical simulation results show that the proposed FIMM algorithm can effectively improve the target state fusion estimation accuracy while maintaining good estimation performance when target motion pattern changes, ensuring the continuous and stable target tracking.
Federated Interactive Multiple Model Filtering for Multi-UAV Cooperative Target Tracking
Lect. Notes Electrical Eng.
International Conference on Guidance, Navigation and Control ; 2024 ; Changsha, China August 09, 2024 - August 11, 2024
02.03.2025
12 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
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