高斯平滑模糊函数和sDAE_LIBSVM的LPI雷达调制样式识别  

LPI Radar Modulation Recognition Based on Gaussian Smoothing Ambiguity Function and sDAE_LIBSVM

作　　者：吴力华 杨露菁[1] 袁园 WU Lihua;YANG Lujing;YUAN Yuan(School of Electronic Engineering Naval University of Engineering,Wuhan 430000 China;Luoyang Electronic Equipment Test Center,Luoyang 471000 China)

机构地区：[1]海军工程大学电子工程学院,武汉430000 [2]中国洛阳电子装备试验中心,河南洛阳471000

出　　处：《电光与控制》2022年第11期31-37,共7页Electronics Optics & Control

基　　金：国家自然科学基金(41774021,41974005)。

摘　　要：结合典型LPI雷达信号的特点和调制样式识别的需求,提出了一种基于高斯平滑模糊函数和sDAE_LIBSVM的调制样式识别方法。首先,采用模糊函数变换结合高斯平滑,完成特征图像的构建;其次,通过融合栈式降噪自编码器(sDAE)和LIBSVM搭建识别网络,用于特征图像的分类识别。仿真实验可知,所提方法在SNR为-7 dB时,对BPSK,Costas,Frank,LFM及T1~T4共8类LPI雷达典型调制样式能达到97%的成功识别概率,并具有较强的稳定性和鲁棒性,相比其他方法具有更好的识别性能。With the characteristics of typical LPI radar signals and the requirements for modulation pattern recognition a method of modulation recognition for typical LPI radar signal based on Gaussian smoothing ambiguity function and sDAE_LIBSVM is proposed.Firstly the ambiguity function transformation combined with Gaussian smoothing is adopted to complete the construction of feature images.Secondly a recognition network is built with the fusing of stack Denoising AutoEncoder(sDAE)and LIBSVM which is used for the classification and recognition of feature images.The simulation results show that when SNR is-7 dB the Probability of Successful Recognition(PSR)of the proposed method can achieve 97%for eight typical modulation patterns of LPI radars including BPSK Costas Frank LFM and T1~T4 and it has strong stability and robustness.Compared with other methods it has better recognition performance.

关 键 词：雷达信号 调制识别 高斯平滑 模糊函数 sDAE LIBSVM 低截获概率 AFI 

分 类 号：TN957.51[电子电信—信号与信息处理]