Research on Parameter Construction Method of Blue Army Equipment Model Based on a Deep Network

doi:10.16182/j.issn1004731x.joss.22-FZ0915

Abstract

Abstract:

The modeling of blue army equipment is an indispensable part of adversarial simulation environment construction. Aiming at the limited available parameters of "information-poor" and "small sample" characteristics to the blue system, a deep network-based method is proposed to generate the parameters of blue army equipment model. By injecting the information into the simulation model of the blue army equipment, the simulation data is generated and trained in the deep neural network. The obtained network has a certain generalization ability to the unknown parameters prediction of the same type of equipment and can be used directly in prediction or be the source model for migration learning. The application is verified by the modeling simulation of a certain type of interceptor of blue army in which two kinds of networks, multilayer perceptron and recurrent neural network, are used to learn and predict the proportional guidance coefficients, and the results are good.

Key words: blue army model parameters, grey system modeling, simulation model, deep network, interceptor modeling

CLC Number:

TP391.9

Boyuan Zhang, Guanghong Gong, Ze Wang, Ni Li. Research on Parameter Construction Method of Blue Army Equipment Model Based on a Deep Network[J]. Journal of System Simulation, 2022, 34(12): 2629-2638.

Figures/Tables 14

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Table 2

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变量名	含义
M_totalmass	导弹的总质量
a	垂直发射的加速度
a1	火箭第一段推力加速度
M_twosteplossrate	第一级火箭燃料燃烧率
Destroyrange	导弹的毁伤半径
M_proportionalCoef	比例导引系数
M_maxliftoverload	导弹的最大升力过载

变量	含义
my_step	导弹状态
lock	是否锁定目标
H	脱靶量
M_T_Dis_TRUE	弹目真实距离
M_v	导弹速度
Mposition.x	导弹位置x轴分量
Mposition.y	导弹位置y轴分量
Mposition.z	导弹位置z轴分量
target_Posture0.x	目标位置x轴分量
target_Posture0.y	目标位置y轴分量
target_Posture0.z	目标位置z轴分量
M_T_R	导弹与目标距离
Mattitude.pitch	导弹俯仰角
Mattitude.yaw	导弹偏航角
Mattitude.roll	导弹滚转角

比例导引系数	所属类别
2.32	3
2.82	8
3.61	16
4.73	27
5.89	39

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