航空学报2026，Vol.47Issue(4)：211-226,16.DOI:10.7527/S1000-6893.2025.32205
基于全域火力场的超视距空战威胁预测及动态逃逸方法
Beyond-visual-range air combat threat prediction and dynamic evasion method based on all-domain fire field theory
摘要
Abstract
To address the threat prediction issue in beyond-visual-range air combat situational awareness,a global fire field-based threat prediction and dynamic evasion methodology is proposed.Firstly,a vector field theory-driven all-domain fire field modeling framework is established,formally defining the concepts and mathematical models of single-aircraft all-domain fire field,joint all-domain fire field,and their corresponding evasion fields.Subsequently,a real-time fire field computation method based on Multi-modal Residual Fusion Network(MRFNet)is developed,which resolves the computational bottlenecks and discrete field distortion issues inherent in traditional Monte Carlo approaches via an"offline training-online inference"deep learning paradigm.Concurrently,a short-term trajectory prediction algorithm employing a Vector Autoregressive Model(VAR)is introduced to enable real-time forecasting of multivariate flight states for both adversarial and friendly aircraft.The proposed methodology allows real-time computation of global and local threat assessments in complex distributed combat scenarios,providing targeted threat warnings and evasion rec-ommendations.Experimental results demonstrate that the MRFNet-based approach reduces single fire field computa-tion time from minute-level to millisecond-level while maintaining fitting errors below 5×10-4,exhibiting excellent data smoothing and extrapolation generalization capabilities.The VAR-based trajectory prediction achieves longitude/lati-tude errors below 8.73×10-4,outperforming various state-of-the-art deep learning-based time series prediction meth-ods,with relative error losses remaining under 22%under strong positional deviation interference in threat detection.Comprehensive simulation analyses confirm that the proposed methodology aligns with pilots'cognitive logic in real combat scenarios,demonstrating high fault tolerance,strong robustness,and low latency characteristics.This work shows significant practical value and operational relevance for adapting to complex distributed combat environments.关键词
全域火力场/态势认知/超视距空战/威胁预测/动态逃逸/深度学习Key words
all-domain fire field/situational awareness/beyond-visual-range air combat/threat prediction/dynamic evasion/deep learning分类
航空航天引用本文复制引用
李乐言,杨任农,郭安新,宋祺,左家亮..基于全域火力场的超视距空战威胁预测及动态逃逸方法[J].航空学报,2026,47(4):211-226,16.基金项目
西安市青年人才托举计划(0959202513098)Young Talent Fund of Xi'an Association for Science and Technology(0959202513098) （0959202513098）
