基于贝叶斯网络的空间群目标意图识别方法

doi:10.12305/j.issn.1001-506X.2026.05.20

Abstract

Abstract:

Existing space target intent recognition methods are limited to single targets and struggle to distinguish the intents of space group targets. To address this issue, an intent recognition method tailored for space group targets is proposed. Firstly, the motion characteristics of space group targets are analyzed and an intent feature set is constructed based on four dimensions: formation pattern, target types, state layer, and action layer. Next, a fuzzy processing method is developed for continuous target features, employing data clustering to create fuzzy membership functions for dynamic adjustment of membership degree of continuous features. Finally, scenes are categorized into near-distance and far-distance based on relative distance. By mining multi-period feature data of group targets in different scenarios, sequential rules are established between formation sub-intents and group intents. A space group target intent recognition model is constructed using dynamic sequence Bayesian networks and its effectiveness and superiority are validated across various scenarios. Experimental results show that the proposed method improves accuracy by 12.50% compared to fuzzy reasoning-based methods, demonstrating the effectiveness of the proposed methed.

Key words: space group target, intent recognition, Bayesian network, fuzzy logic

CLC Number:

V 19

Xuan LIU, Xiaoxia WANG, Fengbao YANG, Bo LI, Yingkai TAO. Bayesian network-based method for space group target intent recognition[J]. Systems Engineering and Electronics, 2026, 48(5): 1635-1646.

Figures/Tables 24

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References 33

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名称	状态集划分
相对速度	慢，中，快
相对距离	近，中，远
飞行方向	正向，反向
轨道阶段	抵近，保持，飞离
目标姿态	三轴稳定，自旋稳定，翻滚状态
干扰状态	开，关
编队队形	椭圆，同心双椭圆，球面，三角形，无
目标类型	探测，评估，控制

输入特征	特征状态	相对运动状态
输入特征	特征状态	逼近	绕飞	跟飞	在轨机动	远离
相对速度	慢	0.1	0.1	0.3	0.2	0.2
	中	0.3	0.8	0.6	0.7	0.3
	快	0.6	0.1	0.1	0.1	0.5
相对距离	近	0.1	0.7	0.6	0.3	0.6
	中	0.3	0.2	0.3	0.4	0.3
	远	0.6	0.1	0.1	0.3	0.1
干扰状态	开	0.5	0.8	0.7	0.5	0.5
干扰状态	关	0.5	0.2	0.3	0.5	0.5
飞行方向	正向	1	0.5	0.7	0.5	0
飞行方向	反向	0	0.5	0.3	0.5	1
目标姿态	三轴稳定	0.1	0.8	0.7	0.7	0.1
	自旋稳定	0.9	0.2	0.3	0.2	0.6
	翻滚状态	0	0	0	0.1	0.3
轨道阶段	抵近	0.6	0.1	0.2	0.1	0
	保持	0.4	0.8	0.7	0.7	0.4
	飞离	0	0.1	0.1	0.2	0.6
目标类型	探测	0.5	0.6	0.6	0.2	0.3
	评估	0.2	0.1	0.2	0.6	0.4
	控制	0.3	0.3	0.2	0.2	0.3
编队队形	椭圆	0.2	0.3	0.2	0.1	0.2
	同心双椭圆	0.1	0.3	0.3	0.2	0.1
	球面	0.2	0.3	0.2	0.2	0.1
	三角形	0.3	0.2	0.2	0.1	0.2
	无	0.25	0.25	0.25	0.25	0.25

相对运动状态	逼近	绕飞	跟飞	在轨机动	远离
逼近	0.3	0.2	0.2	0.2	0.1
绕飞	0.1	0.3	0.2	0.2	0.2
跟飞	0.2	0.2	0.3	0.1	0.2
在轨机动	0.2	0.2	0.1	0.3	0.2
远离	0	0.1	0.1	0.3	0.5

子意图	相对运动状态序列
抵近探测	$ {m}_{1}-{m}_{1}-{m}_{2} $
巡航探查	$ {m}_{1}-{m}_{4}-{m}_{1} $
近距后撤	$ {m}_{4}-{m}_{5}-{m}_{4} $
电磁干扰	$ {m}_{1}-{m}_{1}-{m}_{3} $

输入特征	特征状态	相对运动状态
输入特征	特征状态	逼近	在轨机动	远离
相对速度	慢	0.1	0.2	0.3
	中	0.1	0.7	0.4
	快	0.8	0.1	0.3
相对距离	近	0.1	0.3	0.6
	中	0.3	0.4	0.3
	远	0.6	0.3	0.1
飞行方向	正向	1	0.5	0.7
飞行方向	反向	0	0.5	0.3
轨道阶段	抵近	0.6	0.1	0
	保持	0.4	0.7	0.3
	飞离	0	0.2	0.7
编队队形	椭圆	0.2	0.1	0.2
	同心双椭圆	0.1	0.3	0.2
	球面	0.2	0.3	0.1
	三角形	0.3	0.2	0.3
	无	0.2	0.1	0.2

Bayesian network-based method for space group target intent recognition

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Figures/Tables 24

References 33

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实验方法	时间复杂度	空间复杂度
DSBN（本文方法）	$ O(F M+F S+T {S}^{2}+{S}^{2}) $	$ O(F M+2 {S}^{2}+S T+2 S) $
模糊推理	$ O(F M+F S) $	$ O(F M+S) $

实验方法	单次平均时间/s	平均内存占用/MB
DSBN（本文方法）	0.873	36.43
模糊推理	0.832	16.37

规模等级	准确率/%	单次平均时间/s
中小规模空间目标群	91.50	0.873
大规模空间目标群	87.00	1.171

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子意图	相对运动状态序列
探测	$ {m}_{1}-{m}_{1}-{m}_{4} $
巡航	$ {m}_{1}-{m}_{4}-{m}_{4} $
撤退	$ {m}_{5}-{m}_{5}-{m}_{5} $

终意图	概率
探测	0.007 5
巡航	0
干扰	0.992 5
撤离	0

终意图	概率
探测	0.887 8
巡航	0.112 2
撤离	0

算法	准确率
本文算法	91.50
模糊推理	79.00