基于时频能量谱纹理特征的跳频调制方式识别

TN971; 针对跳频通信调制方式识别问题,提出了一种基于时频能量谱纹理特征的跳频调制方式识别方法.该方法首先采用平滑伪Wigner-Ville分布算法获取跳频信号时频图,并经过二维维纳滤波去除时频图背景噪声,提高低信噪比条件下时频图清晰度;然后采用连通域检测算法提取每跳信号的时频能量谱并将其转化为时频灰度图,计算其直方图统计特征和灰度共生矩阵特征组成22维特征向量;最后通过参数优化后的支持向量机分类器对特征集进行训练、分类和识别.仿真实验表明,所提取的多维特征向量具有较强的表征能力,避免了由单一特征相似性引起的误判问题,在信噪比为-4 dB的条件下,对跳频信号BPSK、QPSK、SDPSK、...

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Published in通信学报 Vol. 40; no. 10; pp. 20 - 29
Main Authors 李红光, 郭英, 眭萍, 齐子森
Format Journal Article
LanguageChinese
Published 空军工程大学信息与导航学院,陕西西安,710077 25.10.2019
Subjects
时频灰度图
跳频调制识别
直方图统计
时频能量谱
灰度共生矩阵
Online AccessGet full text
ISSN1000-436X
DOI10.11959/j.issn.1000-436x.2019191

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Abstract TN971; 针对跳频通信调制方式识别问题,提出了一种基于时频能量谱纹理特征的跳频调制方式识别方法.该方法首先采用平滑伪Wigner-Ville分布算法获取跳频信号时频图,并经过二维维纳滤波去除时频图背景噪声,提高低信噪比条件下时频图清晰度;然后采用连通域检测算法提取每跳信号的时频能量谱并将其转化为时频灰度图,计算其直方图统计特征和灰度共生矩阵特征组成22维特征向量;最后通过参数优化后的支持向量机分类器对特征集进行训练、分类和识别.仿真实验表明,所提取的多维特征向量具有较强的表征能力,避免了由单一特征相似性引起的误判问题,在信噪比为-4 dB的条件下,对跳频信号BPSK、QPSK、SDPSK、QASK、64QAM和GMSK共6种调制方式的平均识别正确率达到91.4％.
AbstractList TN971; 针对跳频通信调制方式识别问题,提出了一种基于时频能量谱纹理特征的跳频调制方式识别方法.该方法首先采用平滑伪Wigner-Ville分布算法获取跳频信号时频图,并经过二维维纳滤波去除时频图背景噪声,提高低信噪比条件下时频图清晰度;然后采用连通域检测算法提取每跳信号的时频能量谱并将其转化为时频灰度图,计算其直方图统计特征和灰度共生矩阵特征组成22维特征向量;最后通过参数优化后的支持向量机分类器对特征集进行训练、分类和识别.仿真实验表明,所提取的多维特征向量具有较强的表征能力,避免了由单一特征相似性引起的误判问题,在信噪比为-4 dB的条件下,对跳频信号BPSK、QPSK、SDPSK、QASK、64QAM和GMSK共6种调制方式的平均识别正确率达到91.4％.
Author 李红光
郭英
眭萍
齐子森
AuthorAffiliation 空军工程大学信息与导航学院,陕西西安,710077
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QI Zisen
SUI Ping
LI Hongguang
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DocumentTitle_FL Frequency hopping modulation recognition based on time-frequency energy spectrum texture feature
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Keywords 时频灰度图
跳频调制识别
直方图统计
时频能量谱
灰度共生矩阵
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Snippet TN971; 针对跳频通信调制方式识别问题,提出了一种基于时频能量谱纹理特征的跳频调制方式识别方法.该方法首先采用平滑伪Wigner-Ville分布算法获取跳频信号时频图,并经过二...
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Title 基于时频能量谱纹理特征的跳频调制方式识别
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