Multi-sensor data fusion for UAV landing guidance based on bayes estimation

Lv Mingwei; Yifan Li; Jinwen Hu; Chunhui Zhao; Xiaolei Hou; Zhao Xu; Quan Pan; Caijuan Jia

doi:10.1109/ICUS50048.2020.9274904

Multi-sensor data fusion for UAV landing guidance based on bayes estimation

Lv Mingwei
, Yifan Li
, Jinwen Hu
, Chunhui Zhao
, Xiaolei Hou
, Zhao Xu
, Quan Pan
, Caijuan Jia

Design and Research Institute
Polytechnical University
Xi'An ASN Technology Group CO.LTD

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

5 Scopus citations

Abstract

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.

Original language	English
Title of host publication	Proceedings of 2020 3rd International Conference on Unmanned Systems, ICUS 2020
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	721-726
Number of pages	6
ISBN (Electronic)	9781728180250
DOIs	https://doi.org/10.1109/ICUS50048.2020.9274904
State	Published - 27 Nov 2020
Externally published	Yes
Event	3rd International Conference on Unmanned Systems, ICUS 2020 - Harbin, China Duration: 27 Nov 2020 → 28 Nov 2020

Publication series

Name	Proceedings of 2020 3rd International Conference on Unmanned Systems, ICUS 2020

Conference

Conference	3rd International Conference on Unmanned Systems, ICUS 2020
Country/Territory	China
City	Harbin
Period	27/11/20 → 28/11/20

Keywords

Bayes estimation
Multi-sensor data fusion
Redundancy technology
UAV autonomous landing

Access to Document

10.1109/ICUS50048.2020.9274904

Cite this

Mingwei, L., Li, Y., Hu, J., Zhao, C., Hou, X., Xu, Z., Pan, Q., & Jia, C. (2020). Multi-sensor data fusion for UAV landing guidance based on bayes estimation. In Proceedings of 2020 3rd International Conference on Unmanned Systems, ICUS 2020 (pp. 721-726). Article 9274904 (Proceedings of 2020 3rd International Conference on Unmanned Systems, ICUS 2020). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICUS50048.2020.9274904

@inproceedings{4ec17ed0c1214748972d038985de3455,

title = "Multi-sensor data fusion for UAV landing guidance based on bayes estimation",

abstract = "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.",

keywords = "Bayes estimation, Multi-sensor data fusion, Redundancy technology, UAV autonomous landing",

author = "Lv Mingwei and Yifan Li and Jinwen Hu and Chunhui Zhao and Xiaolei Hou and Zhao Xu and Quan Pan and Caijuan Jia",

note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 3rd International Conference on Unmanned Systems, ICUS 2020 ; Conference date: 27-11-2020 Through 28-11-2020",

year = "2020",

month = nov,

day = "27",

doi = "10.1109/ICUS50048.2020.9274904",

language = "英语",

series = "Proceedings of 2020 3rd International Conference on Unmanned Systems, ICUS 2020",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "721--726",

booktitle = "Proceedings of 2020 3rd International Conference on Unmanned Systems, ICUS 2020",

}

Mingwei, L, Li, Y, Hu, J , Zhao, C, Hou, X, Xu, Z , Pan, Q & Jia, C 2020, Multi-sensor data fusion for UAV landing guidance based on bayes estimation. in Proceedings of 2020 3rd International Conference on Unmanned Systems, ICUS 2020., 9274904, Proceedings of 2020 3rd International Conference on Unmanned Systems, ICUS 2020, Institute of Electrical and Electronics Engineers Inc., pp. 721-726, 3rd International Conference on Unmanned Systems, ICUS 2020, Harbin, China, 27/11/20. https://doi.org/10.1109/ICUS50048.2020.9274904

Multi-sensor data fusion for UAV landing guidance based on bayes estimation. / Mingwei, Lv; Li, Yifan; Hu, Jinwen et al.
Proceedings of 2020 3rd International Conference on Unmanned Systems, ICUS 2020. Institute of Electrical and Electronics Engineers Inc., 2020. p. 721-726 9274904 (Proceedings of 2020 3rd International Conference on Unmanned Systems, ICUS 2020).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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

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

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ER -

Mingwei L, Li Y, Hu J , Zhao C, Hou X, Xu Z et al. Multi-sensor data fusion for UAV landing guidance based on bayes estimation. In Proceedings of 2020 3rd International Conference on Unmanned Systems, ICUS 2020. Institute of Electrical and Electronics Engineers Inc. 2020. p. 721-726. 9274904. (Proceedings of 2020 3rd International Conference on Unmanned Systems, ICUS 2020). doi: 10.1109/ICUS50048.2020.9274904

Multi-sensor data fusion for UAV landing guidance based on bayes estimation

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