Drones have become an indispensable tool in modern information-based combat systems. In the Russian-Ukrainian conflict, both sides have extensively utilized unmanned aerial vehicles (UAVs) for high-intensity offensive and defensive confrontations, highlighting the crucial role of drones in contemporary warfare. This paper focuses on exploring the practical applications of UAV technology and delves into the intricacies of UAV intention recognition. It proposes a novel method, Transformer-Long Short Term Memory (TLSTM), to enhance the accuracy of UAV combat intention recognition. Through rigorous evaluation and comparison with various deep learning techniques, TLSTM demonstrates exceptional performance, achieving an impressive intention recognition accuracy of 98.59%. These findings have significant implications for assisting commanders in making critical decisions, thereby enhancing the effectiveness of military operations.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    TLSTM: A Transformer-LSTM Method for UAV Combat Intent Recognition


    Weitere Titelangaben:

    Lect. Notes Electrical Eng.


    Beteiligte:
    Song, Yafei (Autor:in) / Wang, Ke (Autor:in) / Li, Lemin (Autor:in) / Li, Chenghai (Autor:in)

    Kongress:

    China Conference on Command and Control ; 2024 ; Beijing, China May 16, 2024 - May 18, 2024



    Erscheinungsdatum :

    31.01.2025


    Format / Umfang :

    15 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




    LSTM-Based UAV Swarm Trajectory Prediction and Intent Recognition

    Ma, Dianqiu / Fu, Xianyi / Huang, Xueqin et al. | IEEE | 2025


    An LSTM-based Intent Detector for Conversational Recommender Systems

    Jbene, Mourad / Tigani, Smail / Saadane, Rachid et al. | IEEE | 2022


    Driving intent recognition

    GLASER STEFAN / ENGEL MARTIN | Europäisches Patentamt | 2022

    Freier Zugriff

    Intent Recognition from Speech and Plan Recognition

    Michele Persiani / Thomas Hellström | BASE | 2021

    Freier Zugriff

    Intent prediction of vulnerable road users from motion trajectories using stacked LSTM network

    Saleh, Khaled / Hossny, Mohammed / Nahavandi, Saeid | IEEE | 2017