Paper Type |
Contributed Paper |
Title |
A Target Tracking Method Based on the Self-organizing Fuzzy Extended Kalman Filter for UAV |
Author |
Zhiyong LIU, Yong ZHAO, Ying JIN and Yulu Wang |
Email |
waljxzy@163.com |
Abstract: This paper proposed a novel approach based on integrated tracking and positioning for Unmanned Aerial Vehicle (UAV) systems. In the proposed scheme, a self-organizing fuzzy Extended Kalman Filter (EKF) system was studied to track the flight trajectory of an UAV. With this goal, the control model of the UAV system with the disturbances was established based on the dynamic equation firstly. Secondly, the self-organizing Fuzzy EKF system was designed to identify and estimate the errors of the UAV position adaptively. And then, the trajectory tracking control was determined for the UAV according to the obtained errors. Finally, the proposed strategy was applied to a UAV to demonstrate the effectiveness. |
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Article ID |
e2024073 |
Received Date |
2023-11-21 |
Revised Date |
2024-04-29 |
Accepted Date |
2024-06-25 |
Full Text |
Download |
Keyword |
self-organizing fuzzy system, extended Kalman filter(EKF), unmanned aerial vehicle (UAV), tracking and positioning |
Volume |
Vol.51 No.5 (September 2024) |
DOI |
https://doi.org/10.12982/CMJS.2024.073 |
Citation |
Liu Z., Zhao Y., Jin Y. and Wang Y., A Target Tracking Method Based on the Self-organizing Fuzzy Extended Kalman Filter for UAV, Chiang Mai J. Sci., 2024; 51(5): e2024073. DOI 10.12982/CMJS.2024.073. |
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