信号处理2025，Vol.41Issue(11)：1775-1787,13.DOI:10.12466/xhcl.2025.11.004
基于改进Transformer的天波超视距雷达目标跟踪方法
Target Tracking Method Based on Improved Transformer for Skywave Over-the-Horizon Radar
摘要
Abstract
Skywave over-the-horizon radar(OTHR)has unique advantages in remote target detection and tracking;however,it also has the disadvantages of low measurement accuracy and difficult target tracking.To this end,this paper proposes a target-tracking approach in the OTHR measurement coordinate system,namely the dual-channel feature fu-sion transformer network(DcFFTNet).DcFFTNet uses a dual-channel feature fusion module to extract target trajectory sequence information from different dimensions.It constructs feature vectors for each time step of the entire trajectory se-quence,ensuring that the features from each dimension can be fully expressed.This enables a more comprehensive de-scription of the target's motion state and characteristics.Moreover,DcFFTNet uses a multi-head deformable attention mechanism to adaptively focus on crucial parts of the trajectory sequence,thereby better capturing critical measurement information during the tracking process.Consequently,this method enhances the feature representation of trajectory se-quences and enables adaptive information extraction,thus making it effective for tracking targets detected by OTHR.To facilitate the training and testing of the network model,this study developed a target trajectory generator.Based on the state space model and OTHR measurement model,it creates a dataset of target trajectory samples with combined motion patterns of constant velocity and constant turn-rate.Simulations show that the approach in this paper outperforms mod-els,such as the unscented Kalman filter and long short-term memory networks in tracking accuracy.关键词
天波超视距雷达/目标跟踪/Transformer/双通道特征融合/多头可变形注意力Key words
skywave over-the-horizon radar/target tracking/Transformer/dual-channel feature fusion/multi-head deformable attention分类
信息技术与安全科学引用本文复制引用
罗忠涛,罗瑞,齐浩楠,陈琦..基于改进Transformer的天波超视距雷达目标跟踪方法[J].信号处理,2025,41(11):1775-1787,13.基金项目
重庆市自然科学基金面上项目(CSTB2024NSCQ-MSX0396) （CSTB2024NSCQ-MSX0396）
重庆市教委科学技术研究项目(KJQN202300633)The Chongqing Natural Science Foundation General Project(CSTB2024NSCQ-MSX0396) （KJQN202300633）
The Science and Technology Research Program of Chongqing Municipal Education Commission(KJQN202300633) （KJQN202300633）
