Hypersonic vehicle in near space has penetration capability with a large range and strong maneuvering, which leads to a non-inertial trajectory and a great threat to the anti-missile interception system. Accurate prediction of the target trajectory can provide strong support for effective interception. In this paper, an intelligent neural network prediction model based on LSTM is proposed for the slippage leap trajectory of hypersonic vehicles, achieving high accuracy prediction of target trajectory. The target trajectory data set is constructed by a hypersonic high-precision simulation model. Taking the three-dimensional position, velocity, trajectory inclination, and angle of attack as the six-dimensional input features, the LSTM network is trained to predict the expected position of the target in a period to come. The experimental results show that the LSTM network constructed in this paper can effectively predict the slippage leap trajectory of hypersonic vehicles with acceptable errors, and can provide a favorable reference for anti-missile interception system.


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    Title :

    Intelligent Trajectory Predicting of Hypersonic Vehicle Using LSTM


    Additional title:

    Lect. Notes Electrical Eng.


    Contributors:
    Fu, Wenxing (editor) / Gu, Mancang (editor) / Niu, Yifeng (editor) / Yuanjie, Meng (author) / Chunqiao, Dan (author) / Jin, Zhang (author) / Xiaomeng, Bai (author) / Tianxing, Cai (author)

    Conference:

    International Conference on Autonomous Unmanned Systems ; 2022 ; Xi'an, China September 23, 2022 - September 25, 2022



    Publication date :

    2023-03-10


    Size :

    13 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




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