电波科学学报2025，Vol.40Issue(2)：201-211,11.DOI:10.12265/j.cjors.2024205
基于LPI-U-Net的端到端时域低截获概率雷达信号增强
LPI-U-Net-based end-to-end time-domain LPI radar signal enhancement
摘要
Abstract
Low probability of intercept(LPI)radar signals are widely used in modern electronic warfare due to their excellent anti-intercept capability.The low peak power of LPI radar signals makes them easily overwhelmed by additive white Gaussian noise(AWGN),which results in low signal-to-noise ratio(SNR),and poses a great challenge for signal detection and identification.In order to extract the original LPI radar signals from the AWGN background,this paper proposes a deep neural network(DNN)called LPI-U-Net for end-to-end time-domain LPI radar signal enhancement.The network consists of a feature extract module(FEM),a feature focus module(FFM)and a signal recover module(SRM).First the FEM extracts the features of the signal by convolution operation,then the FFM uses convolution and inter-channel attention to further focus on the features that are beneficial to the signal enhancement task,and finally the SRM reconstructs the signal from the features by using the deconvolution operation,thus completing the LPI radar signal enhancement.Simulation experiments show that the performance of LPI-U-Net for LPI radar signal enhancement at low SNR outperforms typical noise reduction methods in conventional signal processing,verifying its feasibility and effectiveness.关键词
低截获概率(LPI)雷达信号增强/LPI-U-Net/深度学习/卷积神经网络/通道间注意力Key words
low probability of interception(LPI)radar signal enhancement/LPI-U-Net/deep learning/convolutional neural networks/channel attention分类
地球科学引用本文复制引用
程晨,孙智,孙本迪,崔国龙..基于LPI-U-Net的端到端时域低截获概率雷达信号增强[J].电波科学学报,2025,40(2):201-211,11.基金项目
国家自然科学基金(62101099) （62101099）
国家自然科学基金青年科学基金(62101099) （62101099）
四川省自然科学基金(2025ZNSFSC1428) （2025ZNSFSC1428）
中国博士后科学基金(2021M690558,2022T150100) （2021M690558,2022T150100）
