计算机工程 ›› 2018, Vol. 44 ›› Issue (7): 285-290,296.doi: 10.19678/j.issn.1000-3428.0047154

• 开发研究与工程应用 • 上一篇    下一篇

基于局部二值模式特征的新型干扰识别算法

杨兴宇,阮怀林   

  1. 国防科技大学 电子对抗学院,合肥 230037
  • 收稿日期:2017-02-21 出版日期:2018-07-15 发布日期:2018-07-15
  • 作者简介:杨兴宇(1993—),男,硕士研究生,主研方向为图像处理、雷达对抗技术;阮怀林,教授、博士、博士生导师。

New Jamming Identification Algorithm Based on Local Binary Pattern Feature

YANG Xingyu,RUAN Huailin   

  1. College of Electronic Countermeasture,National University of Defense Technology,Hefei 230037,China
  • Received:2017-02-21 Online:2018-07-15 Published:2018-07-15

摘要:

为解决频谱弥散干扰和切片组合干扰两种距离假目标新型干扰的识别问题,提出一种基于时频图像局部二值模式特征的干扰识别算法。运用平滑伪魏格纳-维尔分布时频分析雷达接收信号,通过数字图像处理技术对时频图像进行预处理,并利用图像局部二值特征提取图像的纹理特征进行识别。实验结果表明,与基于模糊函数的SMSP和C&I干扰识别算法相比,该算法能有效降低噪声的影响,且在低信噪比下仍具有较好的识别率。

关键词: 新型干扰, 干扰识别, 平滑伪魏格纳-维尔分布, 局部二值模式特征, 特征提取

Abstract:

In order to solve the problem of Smeared Spectrum(SMSP) and Chopping and Interleaving(C&I) new jamming,a new type of interference identification algorithm based on Local Binary Pattern(LBP) feature of time-frequency image is proposed.The algorithm uses a Smoothing Pseudo-Wigner-Weier Distribution(SPWD) time-frequency to analyse the radar received signals,preprocesses the time-frequency images,through digital image processing techniques and uses image local binary features to extract image texture features for recognition.Experimental results show that compared with SMSP and C&I interference recognition algorithm based on ambiguity function,the algorithm can effectively reduce the influence of noise,and still has a becter recognition rate at low Signal to Noise Ratio(SNR).

Key words: new jamming, jamming identification, Smoothing Pseudo-Wigner-Weier Distribution(SPWD), Local Binary Pattern(LBP) feature, feature extraction

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