VIRTUAL TARGET DIFFERENTIAL GAME MIDCOURSE GUIDANCE LAW FOR HYPERSONIC CRUISE MISSILE BASED ON NEURAL NETWORK  

高超声速巡航导弹的神经网络虚拟目标微分对策中制导律(英文)

作　　者：桑保华[1] 姜长生[1] 

机构地区：[1]南京航空航天大学自动化学院

出　　处：《Transactions of Nanjing University of Aeronautics and Astronautics》2008年第2期121-127,共7页南京航空航天大学学报（英文版）

基　　金：国家自然科学基金(90716028)资助项目~~

摘　　要：For the high altitude cruising flight phase of a hypersonic cruise missile （HCM）, a relative motion mod- el between the missile and the target is established by defining virtual target and combining the theory of the dif- ferential geometry with missile motion equations. Based on the model, the motion between the missile and the tar- get is considered as a single target differential game problem, and a new open-loop differential game midcourse guidance law （DGMGL） is deduced by solving the corresponding Hamiltonian Function. Meanwhile, a new struc- ture of a closed-loop DGMGL is presented and the training data for back propagation neural network （BPNN） are designed. By combining the theory of BPNN with the open-loop DGMGL obtained above, the law intelligence is realized. Finally, simulation is carried out and the validity of the law is testified.针对高超声速巡航导弹的高空巡航飞行段,采用虚拟目标的定义方法,结合微分几何知识以及运动学方程建立了导弹与目标的相对运动模型,并在此基础上视其与虚拟目标之间的运动为单目标微分对策问题。利用哈密尔顿函数求解方法推导了开环微分对策中制导律,同时建立了一种新的闭环微分对策中制导律结构图,并对反向传播神经网络的训练样本进行了设计。通过反向传播神经网络的函数逼近功能实现了高超声速巡航导弹微分对策中制导律的智能化。仿真验证表明了其有效性。

关 键 词：missiles TARGETS GUIDES back propagation neural network differential game 

分 类 号：TJ765.3[兵器科学与技术—武器系统与运用工程] V249.3[航空宇航科学与技术—飞行器设计]