现代雷达2026，Vol.48Issue(1)：25-33,9.DOI:10.16592/j.cnki.1004-7859.20240803001
基于DCC-BiLSTM的高频地波雷达海面目标机动状态识别方法
A Maneuvering State Recognition Method for Sea Surface Targets Based on DCC-BiLSTM Model for HFSWR
摘要
Abstract
High-frequency surface wave radar faces challenges in accurately monitoring maneuvering targets due to the complexity and variability of their motion patterns.Inaccurate state estimation is often caused by decision delays and tracking model switching delays,which are typically followed by track fragmentation and loss.To address these issues,a maneuvering state discrimination method com-bining a dilated and causal convolution(DCC)network with a bidirectional long short-term memory(BiLSTM)network is proposed.Firstly,the DCC network is applied to the target state data sequence obtained from target tracking to capture multi-scale spatial fea-tures,which are used for identifying the correlation among various motion state parameters at different time instants.Subsequently,the obtained feature sequences are processed by the BiLSTM network to detect temporal trends and to establish mapping relations be-tween these trends and the target's motion patterns.Through this dual-network architecture,real-time maneuvering state discrimina-tion is enabled,and motion models can be adaptively selected.The effectiveness of the proposed method in recognizing diverse ma-neuvering types is demonstrated by experimental results,with a recognition accuracy of 97%achieved.关键词
高频地波雷达/机动目标跟踪/机动状态识别/膨胀因果卷积/双向长短期记忆网络Key words
HFSWR/maneuvering target tracking/maneuvering state recognition/DCC/BiLSTM分类
信息技术与安全科学引用本文复制引用
孙伟峰,陈雨欣..基于DCC-BiLSTM的高频地波雷达海面目标机动状态识别方法[J].现代雷达,2026,48(1):25-33,9.基金项目
国家自然科学基金资助项目(62071493) （62071493）
山东省自然科学基金资助项目(ZR2024MF056) （ZR2024MF056）
