基于GRU的敌方拦截弹制导律快速辨识方法

Yinhan Wang, Shipeng Fan*, Guang Wu, Jiang Wang, Shaoming He

*此作品的通讯作者

科研成果: 期刊稿件文章同行评审

8 引用 (Scopus)

摘要

To identify the guidance law of enemy interceptor missile, a fast guidance law identification method is proposed based on the Gate Recurrent Unit (GRU). A model for the relative motion of the interceptor missile and aircraft in the three-dimensional space is constructed, and it is assumed that the interceptor adopts the classical PN guidance law or APN guidance law. The training sample set and test sample set are extracted from the model. The input of the samples is the kinematic information of both missile and aircraft, while the label is the guidance law of the missile. A neural network with three hidden layers is established based on the GRU. The back propagation based on Adam is used to train the network. The influence of the elements including noise, sample time span, type and size of neural networks on identification accuracy is investigated by simulation, and parameters of GRU networks are optimized. Simulations are conducted under different conditions. The results show that the method proposed has better performance of anti-noise and higher precision than other types of networks. In addition, compared with the identification model based on Kalman filter, the proposed method can reduce the identification time.

投稿的翻译标题Fast guidance law identification approach for incoming missile based on GRU network
源语言繁体中文
文章编号325024
期刊Hangkong Xuebao/Acta Aeronautica et Astronautica Sinica
43
2
DOI
出版状态已出版 - 25 2月 2022

关键词

  • Augmented proportional navigation
  • GRU network
  • Guidance law identification
  • Neural network
  • Proportional navigation

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