基于多维小波特征的有源雷达欺骗干扰识别  

Active Radar Deception Jamming Recognition Based on Multidimensional Wavelet Features

作　　者：刘一兵[1] 罗强[1] 胡然[1] 付琳琳 LIU Yibing;LUO Qiang;HU Ran;FU Linlin(PLA 63892 Troops,Luoyang 471003,China)

机构地区：[1]中国人民解放军63892部队,河南洛阳471003

出　　处：《现代防御技术》2024年第3期120-127,共8页Modern Defence Technology

摘　　要：针对跟踪工作模式下常见雷达有源欺骗干扰识别问题,通过分析雷达信号和干扰模型,提出一种基于多维小波特征的识别算法。对目标回波多个相干处理间隔中的首个脉冲重复间隔内信号采样累积,构成一维离散序列,利用Mallat算法提取多尺度小波系数,计算不同尺度下小波系数的移位相关系数,并组成特征向量用于分类识别。构建不同参数的信号样本仿真,在信噪比为-5 dB时仍有高于80%的识别正确率。该算法能将距离假目标干扰和距离拖引干扰有效识别,证明了算法的准确性、通用性和严谨性。此外,针对实际情况,可以调整特征向量维度,选择更适合的母小波函数,进一步优化干扰识别效果。According to the identification of radar active deception jamming in tracking mode,by analyzing radar signal and jamming models,we propose a recognition algorithm based on multidimensional wavelet features.The signal is sampled and accumulated within the first pulse repetition interval among multiple coherent processing intervals of the target echo to constitute a one-dimensional discrete sequence and the multi-scale wavelet coefficients are extracted using the Mallat algorithm.The shift correlation coefficients of wavelet coefficients at different scales are computed to constitute eigenvector for recognition.Constructing signal samples with different parameters for simulation,the recognition accuracy is still higher than 80%at the signal-to-noise ratio of-5 dB,and the algorithm can effectively distinguish between the range false target and the range gate pull off jamming,which proves the accuracy,versatility and preciseness of the algorithm.Moreover,for the actual situation,we can adjust the dimensions of eigenvector,and select more suitable mother wavelet to further optimize the jamming recognition result.

关 键 词：雷达有源欺骗干扰 离散小波变换 多尺度分析 特征向量 干扰识别 信噪比 

分 类 号：TN973.1[电子电信—信号与信息处理] TP391.9[电子电信—信息与通信工程] TJ0[自动化与计算机技术—计算机应用技术]