Recognition of LPI radar signal based on dual efficient network  

作　　者：Li Hui Qin Yibo Hou Qinghua Cheng Yuanyang 

机构地区：[1]School of Physics and Electronic Information Engineering,Henan Polytechnic University,Jiaozuo 454000,China

出　　处：《The Journal of China Universities of Posts and Telecommunications》2024年第5期12-22,共11页中国邮电高校学报（英文版）

摘　　要：Addressing the issue of low pulse identification rates for low probability of intercept(LPI)radar signals under low signal-to-noise ratio(SNR)conditions,this paper aims to investigate a new method in the field of deep learning to recognize modulation types of LPI radar signals efficiently.A novel algorithm combining dual efficient network(DEN)and non-local means(NLM)denoising was proposed for the identification and selection of LPI radar signals.Time-domain signals for 12 radar modulation types were simulated,adding Gaussian white noise at various SNRs to replicate complex electronic countermeasure scenarios.On this basis,the noisy radar signals undergo Choi-Williams distribution(CWD)time-frequency transformation,converting the signals into two-dimensional(2D)time-frequency images(TFIs).The TFIs are then denoised using the NLM algorithm.Finally,the denoised data is fed into the designed DEN for training and testing,with the selection results output through a softmax classifier.Simulation results demonstrate that at an SNR of-8 dB,the algorithm can achieve a recognition accuracy of 97.22%for LPI radar signals,exhibiting excellent performance under low SNR conditions.Comparative demonstrations prove that the DEN has good robustness and generalization performance under conditions of small sample sizes.This research provides a novel and effective solution for further improving the accuracy of identification and selection of LPI radar signals.

关 键 词：Choi-Williams distribution(CWD) dual efficient network(DEN) low probability of intercept(LPI)radar signals non-local means(NLM)denoising 

分 类 号：TN957.51[电子电信—信号与信息处理]