利用干扰先验信息提升雷达目标识别在中断采样欺骗干扰下的鲁棒性
Robust HRRP Recognition under Interrupted Sampling Repeater Jamming using a Prior Jamming Information-Guided Network
- 用点扩散函数建模干扰导致的回波失真，作为先验指导网络
- 在模拟与实测数据上均超越现有方法，对未知干扰参数泛化能力强
- 适合对抗电子干扰的雷达目标识别系统研发人员
基于高分辨距离轮廓（HRRP）的雷达自动目标识别（RATR）因能捕捉精细结构特征而备受关注。然而，在电子对抗（ECM）尤其是主流的中断采样重复干扰（ISRJ）下进行目标识别仍面临严峻挑战，因为HRRP常出现严重特征失真。为此，本文提出一种基于先验干扰信息的鲁棒HRRP识别方法。具体地，引入点扩散函数（PSF）作为先验信息，以建模ISRJ引起的HRRP失真。在此基础上，设计一种通过先验引导特征交互模块和混合损失函数增强判别能力的识别网络。借助先验信息，模型可在不同干扰参数下学习到畸变HRRP中的不变特征。仿真与实测数据实验均表明，该方法持续优于当前最优方法，并在面对未见干扰参数时展现出更强泛化能力。
原文摘要 · Abstract (English)
Radar automatic target recognition (RATR) based on high-resolution range profile (HRRP) has attracted increasing attention due to its ability to capture fine-grained structural features. However, recognizing targets under electronic countermeasures (ECM), especially the mainstream interrupted-sampling repeater jamming (ISRJ), remains a significant challenge, as HRRPs often suffer from serious feature distortion. To address this, we propose a robust HRRP recognition method guided by prior jamming information. Specifically, we introduce a point spread function (PSF) as prior information to model the HRRP distortion induced by ISRJ. Based on this, we design a recognition network that leverages this prior through a prior-guided feature interaction module and a hybrid loss function to enhance the model's discriminative capability. With the aid of prior information, the model can learn invariant features within distorted HRRP under different jamming parameters. Both the simulated and measured-data experiments demonstrate that our method consistently outperforms state-of-the-art approaches and exhibits stronger generalization capabilities when facing unseen jamming parameters.
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