为有效规避外军侦察卫星对我海上舰船目标的侦察监视或对其实施干扰抗击，需要对外军卫星轨道进行预测。卫星轨道预报模型局限性及预测精度不高是目前该领域存在的难题，针对传统方法存在的问题，提出一种基于神经网络算法的卫星轨道预报算法，通过训练历史TLE数据得出轨道变化规律，从而预报卫星轨道，初步的实验结果表明，所提出的算法可行。
It is necessary to predict the orbit of foreign military satellites in order to effectively evade the reconnaissance and surveillance of Chinese naval ship targets by foreign military reconnaissance satellitesor to carry out interference countermeasures. The limitation and low prediction accuracy of the satellite orbitprediction model is the problems currently existing in this field. Aiming at the existing problem of the traditional method, this paper proposes a satellite orbit prediction algorithm based on neural network algorithm, and obtain the track change rules by training historical TLE data, which forecast satellite orbit. the preliminary experimental results show that the proposed algorithm is feasible.
2020,42(10): 146-151 收稿日期：2020-07-03
DOI：10.3404/j.issn.1672-7649.2020.10.028
分类号：TP183
作者简介：罗飞(1977-)，男，博士，副研究员，研究方向为海军科技创新、军事运筹学
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