The invention discloses a low-earth-orbit satellite orbit forecasting method and system, a terminal and a medium, and the method comprises the steps: carrying out the dynamic orbit determination calculation of a low-earth-orbit satellite based on satellite-borne GNSS observation data, obtaining the state quantity of the satellite at each historical moment, and taking the calculated state quantity of the satellite at the last moment as the state quantity of the satellite orbit forecasting at the initial moment; inputting a sequence formed by the atmospheric resistance coefficient and the empirical acceleration coefficient at each historical moment into a trained neural network prediction model, and predicting the atmospheric resistance coefficient and the empirical acceleration coefficient at a future moment; and forecasting the low-orbit satellite orbit by using the dynamic model based on the state quantity at the initial moment of satellite orbit forecasting and the predicted atmospheric resistance coefficient and empirical acceleration coefficient. According to the method, accurate prediction of the non-conservative force parameters of the low-orbit satellite is achieved based on the neural network, the two non-conservative force parameters of the atmospheric resistance coefficient and the empirical acceleration coefficient are comprehensively considered, and the orbit prediction accuracy of the low-orbit satellite is improved.

    本发明公开了一种低轨卫星轨道预报方法、系统、终端及介质,其中方法包括:基于星载GNSS观测数据对低轨卫星进行动力学定轨解算处理,获取卫星各历史时刻状态量,并以解算得到的最后时刻的卫星状态量作为卫星轨道预报初始时刻状态量;将各历史时刻的大气阻力系数和经验加速度系数组成的序列输入训练好的神经网络预测模型,预测未来时刻的大气阻力系数和经验加速度系数;基于卫星轨道预报初始时刻状态量及预测的大气阻力系数和经验加速度系数,利用动力学模型对低轨卫星轨道进行预报。本发明基于神经网络的方法实现低轨卫星非保守力参数的精确预测,综合考虑大气阻力系数和经验加速度系数两种非保守力参数,提高了低轨卫星轨道预报精度。


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    Titel :

    Low-orbit satellite orbit forecasting method and system, terminal and medium


    Weitere Titelangaben:

    一种低轨卫星轨道预报方法、系统、终端及介质


    Beteiligte:
    CHEN XIANG (Autor:in) / DAI WUJIAO (Autor:in) / TANG CHENGPAN (Autor:in) / LI KAI (Autor:in) / HU XIAOGONG (Autor:in)

    Erscheinungsdatum :

    19.03.2024


    Medientyp :

    Patent


    Format :

    Elektronische Ressource


    Sprache :

    Chinesisch


    Klassifikation :

    IPC:    G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen / B64G Raumfahrt , COSMONAUTICS / G01S RADIO DIRECTION-FINDING , Funkpeilung



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