空军工程大学学报2024，Vol.25Issue(2)：32-38,7.DOI:10.3969/j.issn.2097-1915.2024.02.004
基于新特征参数的再入滑翔飞行器机动模式智能辨识
Intelligent Recognition of Maneuver Modes for Reentry Gliding Vehicle Based on New Featuse Parameters
摘要
Abstract
The maneuver mode recognition problem of reentry gliding vehicle(RGV)is the key to the in-terceptors in achieving its trajectory prediction.In view of this issue,this paper proposes a set of feature parameters fitted to the maneuver characteristics of vehicle trajectories.Based on the constructed RGV maneuvering mode trajectory library,an LSTM deep learning neural network is built,training the extrac-ted new feature parameters.Compared with the traditional modes recognition method and other typical feature parameters in network training,the results show that the set of the proposed feature parameters is fast at convergence speed,high in recognition accuracy,and good in robustness in LSTM maneuver mode recognition network training.关键词
再入滑翔飞行器/特征参数/机动模式/智能辨识Key words
reentry gliding vehicle/characteristic parameters/maneuver mode/intelligent recognition分类
航空航天引用本文复制引用
贺杨超,李炯,邵雷,周池军,张锦林..基于新特征参数的再入滑翔飞行器机动模式智能辨识[J].空军工程大学学报,2024,25(2):32-38,7.基金项目
国家自然科学基金(62173339) （62173339）
