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.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Multi-sensor Data Fusion for UAV Landing Guidance Based on Bayes Estimation


    Contributors:
    Mingwei, Lv (author) / Li, Yifan (author) / Hu, Jinwen (author) / Zhao, Chunhui (author) / Hou, Xiaolei (author) / Xu, Zhao (author) / Pan, Quan (author) / Jia, Caijuan (author)


    Publication date :

    2020-11-27


    Size :

    328071 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Multi-sensor Data Fusion of UAV Landing System

    Shi, Shasha / Hu, Jinwen / Zhao, Chunhui et al. | Springer Verlag | 2021


    Multi-sensor Data Fusion of UAV Landing System

    Shi, Shasha / Hu, Jinwen / Zhao, Chunhui et al. | TIBKAT | 2022


    High-Altitude Precision Landing by Smartphone Video Guidance Sensor and Sensor Fusion

    Joao Leonardo Silva Cotta / Hector Gutierrez / Ivan R. Bertaska et al. | DOAJ | 2024

    Free access


    Image processing and fusion for landing guidance

    Sweet, Barbara T. / Tiana, Carlo L. | SPIE | 1996