To address the problem of low accuracy of target localization of aircraft clusters, a target trajectory tracking method based on the Kalman filter algorithm is used to simulate the cooperative navigation and localization of multiple aircraft. First, the multi-flight motion model and Kalman filter algorithm are introduced. Then, simulation experiments are carried out for the multiobserver tracking target problem to compare and analyse the importance of sensor accuracy in target tracking, and analogy is made to the study of multi-flight collaborative navigation problem. Finally, the performance of the Extended Kalman Filter (EKF) is verified by simulation experiments to address the non-linearity of the vehicle motion model. The results show that the Kalman filter algorithm reduces the noise interference to a certain extent and effectively improves the tracking accuracy of the target trajectory, which is simple and effective to implement. In order to further investigate the multi-vehicle cooperative navigation and positioning technology, a discussion on the tracking of target trajectories by multiple observatories is carried out, which paves the way for the problem of improving the navigation accuracy from aircraft.
Research on Multi-vehicle Positioning Technology Based on Kalman Filter Algorithm
Lect. Notes Electrical Eng.
International Conference on Autonomous Unmanned Systems ; 2022 ; Xi'an, China September 23, 2022 - September 25, 2022
Proceedings of 2022 International Conference on Autonomous Unmanned Systems (ICAUS 2022) ; Kapitel : 63 ; 687-697
10.03.2023
11 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
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