TY - GEN
T1 - Multi-sensor data fusion for UAV landing guidance based on bayes estimation
AU - Mingwei, Lv
AU - Li, Yifan
AU - Hu, Jinwen
AU - Zhao, Chunhui
AU - Hou, Xiaolei
AU - Xu, Zhao
AU - Pan, Quan
AU - Jia, Caijuan
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/11/27
Y1 - 2020/11/27
N2 - The safety issues in the UAV landing process have recently attracted widespread attention. This paper proposes a multi-sensor data fusion algorithm based on Bayes estimation to achieve precise positioning during the autonomous landing of the drone. This method uses outlier detection, state estimation, and data fusion to analyze and process measurement data from multiple sensors in real time to obtain the best real-time data during the autonomous landing of the drone. The simulation results show that this algorithm has good accuracy and robustness in solving the landing guidance problem, can initially achieve autonomous landing guidance for drones, and also has important reference value for the future realization of carrier-based aircraft autonomous landing and fighter precise guidance.
AB - The safety issues in the UAV landing process have recently attracted widespread attention. This paper proposes a multi-sensor data fusion algorithm based on Bayes estimation to achieve precise positioning during the autonomous landing of the drone. This method uses outlier detection, state estimation, and data fusion to analyze and process measurement data from multiple sensors in real time to obtain the best real-time data during the autonomous landing of the drone. The simulation results show that this algorithm has good accuracy and robustness in solving the landing guidance problem, can initially achieve autonomous landing guidance for drones, and also has important reference value for the future realization of carrier-based aircraft autonomous landing and fighter precise guidance.
KW - Bayes estimation
KW - Multi-sensor data fusion
KW - Redundancy technology
KW - UAV autonomous landing
UR - http://www.scopus.com/inward/record.url?scp=85098986828&partnerID=8YFLogxK
U2 - 10.1109/ICUS50048.2020.9274904
DO - 10.1109/ICUS50048.2020.9274904
M3 - 会议稿件
AN - SCOPUS:85098986828
T3 - Proceedings of 2020 3rd International Conference on Unmanned Systems, ICUS 2020
SP - 721
EP - 726
BT - Proceedings of 2020 3rd International Conference on Unmanned Systems, ICUS 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 3rd International Conference on Unmanned Systems, ICUS 2020
Y2 - 27 November 2020 through 28 November 2020
ER -