Abstract： The neural network is trained for the maneuvering of airbreathing hypersonic missile at extreme overload in the longitudinal plane, based on a large number of dichotomies simulation data; considering the dynamic pressure window and the attack angle window; setting the missile maneuvering initial height, Mach number and mass as neural network inputs, and the maximum value of the maneuvering time that the missile maneuvering with the extreme overload as neural network output. The trained neural network can predict the maximum maneuver time by the initial conditions. On the basis, longitudinal maneuvering penetration method is designed by setting the maximum value of the maneuvering time as the upper bound and random selecting the time that the missile maneuvering with the extreme overload. The feasibility of this method is verified by simulation.
魏黎明, 李晓龙, 赵征, 杜厦, 汪九州. 神经网络在吸气式高超声速导弹突防弹道设计上的应用[J]. 空天防御, 2018, 1(2): 14-17.
Wei Liming, Li Xiaolong, Zhao Zheng, Du Sha, Wang Jiuzhou. Application of Neural Network in Penetration of Air-breathing Hypersonic Missile. Air & Space Defense, 2018, 1(2): 14-17.
