雷达科学与技术2025，Vol.23Issue(2)：192-198,205,8.DOI:10.3969/j.issn.1672-2337.2025.02.010
基于融合网络的HRRP目标识别方法
HRRP Target Recognition Method Based on Fusion Network
摘要
Abstract
High resolution range profile(HRRP)is commonly used in the field of radar automatic target recogni-tion.The data structure of HRRP is complex,and extracting stable and reliable features from it is crucial for HRRP tar-get recognition.This paper proposes a fusion network model for the target recognition of ship HRRP.The model first per-forms preliminary feature extraction through bidirectional encoder representations from transformers(BERT),followed by deep feature extraction through a parallel network.The left branch uses a multi-scale convolutional neural network(MCNN)module to extract local feature information at different scales.The convolution results are optimized by squeeze-and-excitation(SE)to better focus on key information in the data.The right branch employs a bidirectional gated recur-rent unit(BiGRU)to capture long-term dependencies in the sequence.Combined with a multi-head attention module,the correlations between different positions can be better captured.Finally,the results are concatenated to maximize the advantages of different networks and improve the model's classification performance.The experimental results show that the model can effectively learn the features from the HRRP sequences and has good recognition performance.关键词
高分辨距离像/BERT模块/MCNN网络/BiGRU网络Key words
high resolution range profile/BERT module/MCNN network/BiGRU network分类
电子信息工程引用本文复制引用
吴文静,但波,王中训..基于融合网络的HRRP目标识别方法[J].雷达科学与技术,2025,23(2):192-198,205,8.基金项目
国家自然科学基金重点项目(No.62293544) （No.62293544）
