基于FRFT联合SSA滤波的LFM信号干扰信号识别算法分析  

Analysis of LFM Signal Interference Signal Recognition Algorithm Based on FRFT Combined SSA Filtering

作　　者：常宇阳 余建宇[1] CHANG Yuyang;YU Jianyu(Xi'an Institute of Electronic Engineering,Shaanxi 710100,China)

机构地区：[1]西安电子工程研究所,陕西710100

出　　处：《电子技术（上海）》2024年第5期7-9,共3页Electronic Technology

摘　　要：阐述复杂电磁环境下线性调频(LFM)信号干扰识别问题及原因,探讨瞄准式干扰、阻塞式干扰、线性扫频式干扰、灵巧噪声卷积干扰、灵巧噪声乘积干扰、密集假目标干扰、频谱弥散干扰、梳状谱干扰、间歇采样直接转发干扰、间歇采样重复转发干扰、间歇采样循环转发式干扰的分数阶傅立叶变换(FRFT)序列,通过奇异谱分析(SSA)滤波对最佳FRFT序列进行预处理,人工提取特征组成特征向量放入支持向量机(SVM)进行分类识别。This paper describes the interference identification problem of linear frequency modulation(LFM)signals in complex electromagnetic environments,exploring the fractional order Fourier transform(FRFT)sequences of aiming interference,blocking interference,linear sweep interference,agile noise convolution interference,agile noise product interference,dense false target interference,spectrum dispersion interference,comb spectrum interference,intermittent sampling direct forwarding interference,intermittent sampling repeated forwarding interference,and intermittent sampling cyclic forwarding interference.The optimal FRFT sequence is preprocessed through singular spectrum analysis(SSA)filtering,and the feature vectors are manually extracted to form feature vectors and placed in support vectormachines(SvM)forclassification andrecognition.

关 键 词：线性调频信号 干扰识别 特征提取 分数阶傅立叶变换 支持向量机 

分 类 号：TN957.51[电子电信—信号与信息处理] TB559[电子电信—信息与通信工程]