Journal of System Simulation
Abstract
Abstract: In order to realize the effective assessment of air combat targets, a deep learning-based air target threat assessment method is proposed. According to threat characteristics of the air target, the threat attributes of air target faced by electronic countermeasure operation are analyzed from the two perspectives of platform layer and equipment layer, the air target threat assessment index system is constructed, and the air target threat assessment index data set is established. Based on convolutional neural network, a residual structure is introduced to optimize the network, a threat assessment model is established, and the threat ranking of air targets is obtained by using the constructed index data set for training. Through simulation and experimental results, it is verified that the proposed threat assessment method has high accuracy, strong robustness, good applicability and effectiveness, which provides a new idea for threat assessment.
Recommended Citation
Jiang, Dawei; Dong, Yangyang; Zhang, Lidong; Lu, Xiao; and Dong, Chunxi
(2025)
"Research on Air Target Threat Assessment Technology Based on Deep Learning,"
Journal of System Simulation: Vol. 37:
Iss.
3, Article 20.
DOI: 10.16182/j.issn1004731x.joss.23-1323
Available at:
https://dc-china-simulation.researchcommons.org/journal/vol37/iss3/20
First Page
791
Last Page
802
CLC
TP391.9
Recommended Citation
Jiang Dawei, Dong Yangyang, Zhang Lidong, et al. Research on Air Target Threat Assessment Technology Based on Deep Learning[J]. Journal of System Simulation, 2025, 37(3): 791-802.
DOI
10.16182/j.issn1004731x.joss.23-1323
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