The invention relates to a method for determining an initial orbit of a satellite with an embedded physical knowledge neural network, which is used for determining an initial orbit of a short arc segment under an optical observation condition and providing support for subsequent precise orbit determination. The network comprises an encoder-decoder structure, an encoder predicts the motion state of a satellite in an orbit according to observation information, the decoder converts the predicted satellite motion state into an observation value, the prediction accuracy of the encoder is evaluated, physical information of satellite orbit dynamics is introduced into a loss function, and the prediction accuracy of the satellite orbit is improved. And satellite orbit determination based on the neural network is realized. The input of the encoder is the observation angle quantity (namely azimuth angle and pitch angle) of the satellite relative to an observer, the observation time and the position information (namely longitude, latitude and altitude) of the observer; the output of the encoder, namely the input of the decoder, is the absolute motion state quantity (namely the position and the speed of the satellite in a geocentric inertial coordinate system) of the satellite in the orbit and the position information of an observer, and the output of the decoder is the observed quantity of the satellite relative to the observer. When the network is trained, firstly, a decoder is trained by taking a mean square error between a predicted observation value and a real observation value as a loss function, and a transformation relation from a satellite motion state to the observation value is learned; fixing the structure and parameters of a decoder, training the whole encoder-decoder network, calculating the derivative of the predicted satellite absolute state quantity relative to the observation time, and calculating the physical information loss of a speed item and an acceleration item; adding the physical information item loss and the mean square error of the observed quantity, constructing a total loss function, and optimizing network parameters through error back propagation; in the reasoning stage, an encoder network is used for reasoning, and the absolute motion state quantity, predicted by an encoder, of the satellite is converted into an orbit element form, namely, the initial orbit is determined.

    本发明涉及一种内嵌物理知识神经网络的卫星初始轨道确定方法,用于光学观测条件下短弧段初始轨道确定,为后续精密定轨提供支持。该网络包含编码器‑解码器结构,编码器根据观测信息预测轨道中卫星的运动状态,解码器将预测的卫星运动状态转换为观测值,评估编码器预测的准确性,并在损失函数中引入了卫星轨道动力学的物理信息,实现基于神经网络的卫星轨道确定。编码器的输入为卫星相对观测者的观测角度量(即方位角和俯仰角)、观测时间和观测者的位置信息(即经、纬度和海拔),编码器的输出也即解码器的输入为轨道中卫星的绝对运动状态量(即其在地心惯性坐标系中的位置和速度)以及观测者的位置信息,解码器输出为卫星相对观测者的观测量。网络在训练时,首先以预测观测值与真实观测值之间的均方误差作为损失函数训练解码器,学习卫星运动状态到观测值的变换关系;然后固定解码器的结构和参数,训练整个编码器‑解码器网络,计算预测的卫星绝对状态量相对观测时间的导数,并计算速度项和加速度项物理信息损失;将物理信息项损失与观测量的均方误差相加,构建总损失函数,并通过误差反向传播优化网络参数;推理阶段,使用编码器网络进行推理,并将编码器预测的卫星的绝对运动状态量转换为轨道要素形式,即实现初始轨道确定。


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    Title :

    Satellite initial orbit determination method of embedded physical knowledge neural network


    Additional title:

    一种内嵌物理知识神经网络的卫星初始轨道确定方法


    Contributors:
    XUE BINDANG (author) / CHO JUN-CHEOL (author)

    Publication date :

    2025-01-07


    Type of media :

    Patent


    Type of material :

    Electronic Resource


    Language :

    Chinese


    Classification :

    IPC:    G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen / B64G Raumfahrt , COSMONAUTICS



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