逆轨拦截的目标命中点分支预测智能制导算法

doi:10.7527/S1000-6893.2024.30873

Abstract

Abstract:

To achieve the maximum interception terminal velocity when intercepting maneuvering targets in the contra-orbit， this paper constructs a target maneuvering ballistic branch prediction model based on the sequence-to-sequence method， and constructs a deep reinforcement learning intelligent guidance law based on the deep Q-learning algorithm and the bias guidance law. To address the sparse reward problem caused by the training process of the smart guidance law， the prediction-correction method is used to introduce the guidance ratio of the terminal guidance to construct the terminal reward， and the process reward is constructed by combining the physical process and performance indexes. The process reward and terminal reward are combined to improve the training effect. Simulation shows that the target maneuvering ballistic branch prediction model improves the average prediction accuracy of the maneuvering ballistic in the sub-direction by at least 67% compared with the ballistic extrapolation method， and the intelligent guidance law improves the relative interception speed by 67% compared with the baseline guidance law on the premise of meeting the requirements of shift performance and low overload.

Key words: maneuvering target, head-on interception, trajectory prediction, predicted hit point, intelligent guidance law

CLC Number:

Qingcheng WAN, Meng YU, Yubao LI, Yin WANG. Intelligent guidance algorithm for target hit point branch prediction for head-on interception[J]. Acta Aeronautica et Astronautica Sinica, 2024, 45(S1): 730873.

Figures/Tables 14

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参数名称	参数值
神经网络隐含层数	2
状态维度	6
动作维度	15
动作网络学习率	0.05
评价网络学习率	0.05
样本批次大小	128
折扣因子	0.99
探索率	0.7
初始目标点/km	（60，30）
初始目标角度/（°）	60
目标变动时弹目距离/km	10
目标变动范围/km	x∈［60，64］y∈［26，30］
变动目标角度/（°）	70
中末交班时弹目距离/km	7
制导过载上限/g	20
交班速度交会角约束/（°）	［50，90］

参数名称	PNG	OCPNG	DLRG（数据过滤）	DLRG
相对拦截速度/（m·s^-1）	614	1 037	1 739	1 070
最大过载比a/g（无量纲）	8.86	24.85	20	20
交班速度交会角/（°）	16.9	33	51.4	22.5

命中点变动方向	制导律种类	相对拦截速度/（m·s^-1）	速度交会角/（°）
左上方	DRLG	1 784	67.0
x∈［56，60］ km	OCPNG	1 203	72.2
y∈［30，34］ km	PNG	1 120	40.5
左下方	DRLG	1 870	56.0
x∈［56，60］ km	OCPNG	1 163	49.6
y∈［26，30］ km	PNG	753	30.2
右上方	DRLG	1 916	60.2
x∈［60，64］ km	OCPNG	1 208	31.5
y∈［30，34］ km	PNG	987	26.7

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Intelligent guidance algorithm for target hit point branch prediction for head-on interception

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