Combat Intention Recognition of Air Cluster Targets Driven by Data and Knowledge

doi:10.12382/bgxb.2024.0113

Abstract

Abstract:

Aiming at the diverse spatiotemporal characteristics of cluster targets and the excessive reliance of traditional data driven models on empirical samples,this paper proposes an algorithm for combat intent recognition driven by both data and knowledge.A cluster feature vector based on the virtual envelope and minimum bounding rectangle of target formation are constructed to enhance the feature expression of enemy situation data,which takes the cluster characteristics,such as the spatial form of cluster targets,into account.A knowledge model based on military expert experience and a long short-term memory (LSTM) network model with attention mechanism are established then.The knowledge model generates the intent pre-recognition vectors based on constraint rule,while the LSTM network model predicts the residual of intent probability distribution.The fusion ratio of both models is adaptively adjusted by utilizing a learnable residual estimator structure.A multi-objective loss function is designed to control the influence weights of the dual models.Ultimately,the fusion of the dual models overcomes the contradiction between the high accuracy of traditional data models and the insufficient data samples.Experimental results indicate that the proposed method improves the recognition accuracy to about 5.34% and 4.98% compared to LSTM and Attention-LSTM,respectively,and has significantly lower dependence on sample size than traditional data-driven methods.

Key words: cluster targets, combat intent, data driving, knowledge driving, attention mechanism

LI Yangjun, HUANG Qilong, YANG Li, CHEN Xu. Combat Intention Recognition of Air Cluster Targets Driven by Data and Knowledge[J]. Acta Armamentarii, 2025, 46(2): 240113-.

Figures/Tables 14

References 22

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运动学特征	状态特征	电磁频谱特征^[12]
水平位置	方位角	脉冲宽度
速度	航向角	脉冲重复频率
加速度	高度	载波频率

运动学特征	状态特征	电磁频谱特征^[12]
水平位置	方位角	脉冲宽度
速度	航向角	脉冲重复频率
加速度	高度	载波频率

参数	速度/(m·s^-1)	加速度/ (m·s^-2)	高度/m	航向变化率/(°)	脉冲宽度/μs	脉冲重复频率/MHz	载波频率/GHz	意图
典型值	30~50	0.15~1.5	300~1600	0~15	4~8	5~9	1.5~4.5	突防
允许值	20~90	0~1.6	250~2000	0~50	0~12	0~11	0~7.5	突防

参数	速度/(m·s^-1)	加速度/ (m·s^-2)	高度/m	航向变化率/(°)	脉冲宽度/μs	脉冲重复频率/MHz	载波频率/GHz	意图
典型值	30~50	0.15~1.5	300~1600	0~15	4~8	5~9	1.5~4.5	突防
允许值	20~90	0~1.6	250~2000	0~50	0~12	0~11	0~7.5	突防

LSTM	注意力机制	集群特征	残差估计器	准确率/%	标准差/%
P				91.76	0.62
P	P			92.12	0.47
P		P		95.68	0.28
P	P	P		96.32	0.25
P	P	P	P	97.10	0.19