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  • 李艳莉,田 晓.基于积谱矩阵局部二值模式的欺骗干扰识别[J].电讯技术,2015,55(4): - .    [点击复制]
  • LI Yanli,TIAN Xiao.Active deception jamming recognition based on local binary pattern of product spectrum matrix[J].,2015,55(4): - .   [点击复制]
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基于积谱矩阵局部二值模式的欺骗干扰识别
李艳莉,田晓
0
(电子科技大学 成都学院,成都 611731;中国西南电子技术研究所,成都 610036)
摘要:
针对跟踪雷达的三种常见欺骗干扰,提出了一种基于积谱矩阵(SPM)局部二值模式(LBP)的识别算法。首先,计算雷达接收信号不同脉冲重复周期(PRI)的积谱,并将其按照频域和慢时域排列成一个二维积谱矩阵。然后,将图像处理的纹理特征引入到欺骗干扰识别的算法中,采用局部二值模式提取二维积谱矩阵的灰度图像特征。最后,通过仿真实验验证了算法的正确性,当雷达接收信号的信噪比(SNR)大于5 dB时,该欺骗干扰识别算法的平均识别概率优于90%。
关键词:  跟踪雷达  欺骗干扰  干扰识别  积谱矩阵  局部二值模式  纹理特征
DOI:
基金项目:
Active deception jamming recognition based on local binary pattern of product spectrum matrix
LI Yanli,TIAN Xiao
()
Abstract:
A recognition algorithm is proposed based on the local binary pattern(LBP) of the product spectrum matrix(SPM) against the major three types of deception jamming of tracking radar. Firstly,the product spectral of the radar received signal in the different pulse repetition interval(PRI) is calculated,and the product spectral of frequency-slow time is arranged into a two-dimensional SPM. Secondly,the texture features of image processing are introduced into the deception jamming recognition algorithm,and the LBP is used to extract the gray image texture characteristics of the two-dimensional SPM. Finally,the experimental results show that the average recognition accuracy of the proposed deception jamming algorithm is higher than 90% when the signal-to-noise ratio(SNR) is greater than 5 dB.
Key words:  tracking radar  deception jamming  jamming recognition  product spectrum matrix  local binary pattern  texture features
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