哈尔滨工程大学学报2026，Vol.47Issue(5)：1136-1145,10.DOI:10.11990/jheu.202412024
时频域特征融合网络雷达信号检测与识别
Radar signal detection and identification based on time-frequency domain features fusion network
肖易寒 1李本正 1秦长海2
作者信息
- 1. 哈尔滨工程大学 信息与通信工程学院,黑龙江 哈尔滨 150001||哈尔滨工程大学 先进船舶通信与信息技术工业和信息化部重点实验室,黑龙江 哈尔滨 150001
- 2. 中国船舶集团有限公司第七二三研究所,江苏 扬州 225000||上海交通大学 计算机学院,上海 200240
- 折叠
摘要
Abstract
To solve the low accuracy of traditional radar signal detection and recognition in low signal-to-noise ratio environments,this paper proposes an improved method.With the in-phase and quadrature components of radar sig-nals as input,after extracting time-domain features,frequency-domain information is obtained via extended dis-crete Fourier transform,and a feature extraction structure combining channel spatial attention and long short-term memory network is constructed.Cross-attention is used for time-frequency feature fusion,and multi-task learning is adopted to simultaneously complete detection and intra-pulse modulation recognition.Experiments show that at SNR≥-6 dB,both recognition rate and detection probability reach 99%;at-10 dB,the detection probability is 96.17%and recognition accuracy is 96.18%,both superior to existing methods,effectively improving detection and recognition performance in complex environments.关键词
雷达信号检测/雷达调制识别/时频域特征融合/扩展离散傅里叶变换/特征提取/通道空间注意力/交叉注意力/多任务学习/深度学习Key words
radar signal detection/radar modulation recognition/time-frequency domain feature fusion/extended discrete Fourier transform/feature extraction/convolutional block attention module/cross-attention/multi-task learning/deep learning分类
信息技术与安全科学引用本文复制引用
肖易寒,李本正,秦长海..时频域特征融合网络雷达信号检测与识别[J].哈尔滨工程大学学报,2026,47(5):1136-1145,10.
