航空学报2026，Vol.47Issue(8)：264-274,11.DOI:10.7527/S1000-6893.2025.32791
基于频域特征和Transformer的无人机目标跟踪算法
A UAV target tracking algorithm based on frequency-domain feature and transformer
刘芳 1崔静虎 1卢晨阳 1王鑫 2浦昭辉3
作者信息
- 1. 北京工业大学 信息科学技术学院,北京 100124
- 2. 国网北京丰台供电公司,北京 100161
- 3. 国网北京市电力公司信通分公司,北京 100761
- 折叠
摘要
Abstract
With the rapid development of Unmanned Aerial Vehicle(UAV)technology,target tracking has become one of the key techniques in UAV applications.To address challenges such as occlusion,deformation,scale varia-tion,and multi-view changes in UAV target tracking,this paper proposes a UAV target tracking algorithm based on frequency-domain feature and Transformer architecture.First,a distilled Transformer network is employed to extract global spatial features from images,and an adaptive frequency-domain deep network is employed to capture detailed frequency-domain features.meanwhile,a learning image is introduced at the input stage to capture the correlation be-tween the target template and the search region,thereby updating the initial target template and enhancing target rep-resentation.Second,a multi-view invariant feature learning strategy based on mutual information maximization is pro-posed.By maximizing the mutual information between the target template and the search template,a novel loss func-tion is designed to improve the network's robustness against target appearance variations.Finally,the target position is determined according to the feature responses of the learning image.Simulation results demonstrate that the pro-posed algorithm effectively improves UAV target tracking accuracy and exhibits strong robustness under complex scenarios.关键词
机器视觉/无人机/目标跟踪/频域特征/深度网络Key words
machine vision/unmanned aerial vehicle/target tracking/frequency-domain feature/deep network分类
航空航天引用本文复制引用
刘芳,崔静虎,卢晨阳,王鑫,浦昭辉..基于频域特征和Transformer的无人机目标跟踪算法[J].航空学报,2026,47(8):264-274,11.
