基于深度学习的时间角度控制制导律

doi:10.12305/j.issn.1001-506X.2023.11.25

Abstract

Abstract:

A deep learning-based impact time and angle control guidance algorithm is proposed to solve the impact time and angle control problem of missile guidance under aerodynamic force. A predictor module is designed for estimating the exact impact time under optimal impact angle guidance law with realistic aerodynamic characteristics, and a feedforward loop for fusing the theoretical model and deep learning method is presented. An approximate time-to-go is predicted by the theoretical model and the prediction error is estimated by deep neural networks, so that the accuracy of prediction is improved. The impact time error could converge to zero after introducing the exact impact time into guidance law, then the joint control of the impact time and the terminal impact angle is achieved. The simulation results show that the designed guidance algorithm can realize the impact time and angle control more accurately compared with that based on a constant velocity assumption.

Key words: missile guidance, impact time control, impact angle control, deep learning

CLC Number:

TJ765.3

Zichao LIU, Jiang WANG, Shaoming HE. Time and angle control guidance law based on deep learning[J]. Systems Engineering and Electronics, 2023, 45(11): 3579-3587.

Figures/Tables 14

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References 31

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马赫数	C_L^α/rad^－1	C_D0	C_D0^α²/rad^－2
0.4	39.056	0.460 4	39.072
0.6	39.468	0.463 5	39.242
0.8	40.801	0.468 2	40.351
0.9	41.372	0.477 6	41.735

参数	取值范围
初始速度v₀/(m·s^－1)	(100, 400)
初始弹道倾角θ₀/(°)	(-30, 30)
目标攻击角度λ_d/(°)	(-180, 0)
弹体质量m /kg	100
导弹x初始坐标x₀/km	(-20, -5)
导弹y初始坐标y₀/km	(5, 20)
目标x坐标x_T /km	0
目标y坐标y_T /km	0

制导律	飞行时间/s	攻击角度/(°)	终端速度/(m/s)
本文	59.94	89.999 6	286.727 3
文献[3]	60.40	112.170 1	261.113 4
文献[4]	60.01	92.974 2	268.097 4

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Time and angle control guidance law based on deep learning

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