现代防御技术2025，Vol.53Issue(3)：32-41,10.DOI:10.3969/j.issn.1009-086x.2025.03.004
一种HRRP重构识别方法:带标签约束的SDAE-CNN
A Method of HRRP Reconstruction and Recognition:SDAE-CNN with Label Constraints
尹建国 1盛文 2赵蒙 3江河4
作者信息
- 1. 空军预警学院,湖北武汉 430019||中国人民解放军95866部队
- 2. 空军预警学院,湖北武汉 430019
- 3. 中国人民解放军95866部队
- 4. 中国人民解放军93110部队
- 折叠
摘要
Abstract
The high resolution range profile(HRRP)of radar airborne targets is commonly used for target recognition.In practical operation,incomplete data samples and noise interference can present challenges to radar target recognition.To overcome this challenge,this paper combines stacked denoising auto-encoders(SDAE)with label constraints and convolutional neural networks(CNN)for HRRP denoising reconstruction and recognition.SDAE can denoise and reconstruct the HRRP data to enhance the data quality and expand the target dataset.By introducing label constraints in SDAE,the ability to associate the hidden features with the categories they belong to can be strengthened to accelerate the model convergence.The CNN is used to classify the HRRP.Experimental results show that the proposed method in this paper demonstrates superior recognition performance in target recognition under small samples and strong noise scenarios,and is able to overcome the adverse effects of fewer samples and higher noise on HRRP recognition to a certain extent.关键词
高分辨距离像/目标识别/数据不完备/噪声干扰/堆栈去噪自编码器/卷积神经网络Key words
high reslution range profile(HRRP)/target recognition/incomplete data/noise interference/stacked denosing auto-encoders(SDAE)/convolution neural network(CNN)分类
信息技术与安全科学引用本文复制引用
尹建国,盛文,赵蒙,江河..一种HRRP重构识别方法:带标签约束的SDAE-CNN[J].现代防御技术,2025,53(3):32-41,10.
