弹道学报2025，Vol.37Issue(1)：60-67,8.DOI:10.12115/ddxb.2024.08001
融合STFT和多流动态网络的空战轨迹预测方法
Air-combat Trajectory Prediction Method Integrating STFT and Multi-stream Dynamic Network
摘要
Abstract
The complexity and changeability of modern air-combat confrontation makes air-combat decisions fuzzy and changeable.Effective trajectory prediction can greatly improve the accuracy of decision-making.Aiming at the characteristics of complex time series in air-combat trajectory prediction,a trajectory prediction method integrating short-time Fourier transform(STFT)and multi-stream transformer network was proposed to improve the accuracy of predicting air-combat maneuver trajectory.During air-combat maneuvers,the trajectory of aircraft changes frequently and complexly.Therefore,the trajectory data were first preprocessed by high-order difference to eliminate noise and retain the spatiotemporal characteristics of trajectory.Subsequently,the short-time Fourier transform was used to extract frequency-domain features of the preprocessed trajectory and analyze the dynamic changes of the trajectory.In order to better capture the differences between position trajectory and attitude trajectory,a trajectory decoupling strategy was designed to process these two types of trajectories separately.Then,the transformer network based on the multi-stream dynamic attention mechanism was used to process these spatiotemporal features,thereby capturing the deep dependencies in the flight trajectory.The network weights multiple data streams through multi-head attention mechanism,enhancing the model's ability to capture the spatiotemporal dependencies of different data streams.Experimental results show that compared to traditional prediction methods,the proposed method has a 3.88%improvement in prediction accuracy.The combination of STFT and multi-stream transformer effectively improves the prediction accuracy of complex air-combat maneuver trajectory,verifying its applicability in high-precision air-combat scene prediction.关键词
轨迹预测/多维特征处理/短时傅里叶变换Key words
trajectory prediction/multidimensional feature processing/short-time Fourier transform引用本文复制引用
岳圣智,邓向阳,付宇鹏,徐俊,宋婧菡,林远山..融合STFT和多流动态网络的空战轨迹预测方法[J].弹道学报,2025,37(1):60-67,8.基金项目
辽宁省教育厅基本科研项目(LJKZ0730,QL202016) （LJKZ0730,QL202016）
辽宁省自然基金资助计划(2020-KF-12-09) （2020-KF-12-09）
辽宁省重点研发计划(2020JH2/10100043) （2020JH2/10100043）
山东省自然基金青年基金(ZR2024QF094) （ZR2024QF094）
