In contemporary aviation, automated landing technology for aircraft is becoming increasingly vital. Achieving high precision and reliable automated landing, however, requires addressing several technological challenges. One of these challenges is the issue of multi-sensor data fusion. During the aircraft landing process, GPS, radar, and inertial navigation system (INS) are three crucial sensors, providing positional, velocity, and attitude information respectively. Each of these sensors has its own advantages and disadvantages; when used independently, they are susceptible to external environmental interferences and intrinsic errors, resulting in insufficient overall navigation precision. This paper proposes a federated filtering method based on Extended Kalman Filter (EKF) to improve navigation accuracy and enhance system stability through the fusion of multiple sensor data. By thoroughly analyzing multi-sensor errors and conducting simulation experiments, this paper will demonstrate the application effects and advantages of this method in the aircraft landing process, and discuss its theoretical and technical innovations.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Research on Multi-sensor Data Fusion for Carrier Landing Guidance


    Weitere Titelangaben:

    Lect. Notes Electrical Eng.


    Beteiligte:
    Liu, Lianqing (Herausgeber:in) / Niu, Yifeng (Herausgeber:in) / Fu, Wenxing (Herausgeber:in) / Qu, Yi (Herausgeber:in) / Yang, Kechen (Autor:in) / Li, Haochen (Autor:in) / Cao, Dengda (Autor:in) / Zhang, Jiandong (Autor:in) / Yang, Qiming (Autor:in)

    Kongress:

    International Conference on Autonomous Unmanned Systems ; 2024 ; Shenyang, China September 19, 2024 - September 21, 2024



    Erscheinungsdatum :

    03.04.2025


    Format / Umfang :

    11 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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

    Mingwei, Lv / Li, Yifan / Hu, Jinwen et al. | IEEE | 2020


    Multi-sensor Data Fusion of UAV Landing System

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


    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. | British Library Conference Proceedings | 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

    Freier Zugriff