低信噪比下激波信号奇点检测方法
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  • 英文篇名:Detection of shock wave signals using singularity under low SNR conditions
  • 作者:谢维 ; 刘小睿 ; 佟健飞 ; 鲍明 ; 李晓东
  • 英文作者:XIE Wei;LI Xiaorui;TONG Jianfei;BAO Ming;LI Xiaodong;Institue of Acoustics, Chinese Academy of Sciences;University of Chinese Academy of Sciences;
  • 中文刊名:XIBA
  • 英文刊名:Acta Acustica
  • 机构:中国科学院声学研究所;中国科学院大学;
  • 出版日期:2018-07-15
  • 出版单位:声学学报
  • 年:2018
  • 期:v.43
  • 基金:国家自然科学基金项目(11774379);; 中国科学院战略性先导专项项目(XDA06020201)资助
  • 语种:中文;
  • 页:XIBA201804010
  • 页数:9
  • CN:04
  • ISSN:11-2065/O4
  • 分类号:83-91
摘要
针对低信噪比下的激波信号检测问题,利用激波信号奇点在小波变换中的路径传递特征及信号奇点小波系数与噪声小波系数明显幅度差异,提出了一种基于信号奇点的连续小波变换检测算法。仿真实验结果表明,在恒定虚警概率下,该方法检测性能相较于能量检测器能提升约3 dB;实际数据实验结果说明,该方法在-3 dB信噪比下检测性能明显优于能量检测器和传统小波多尺度积检测器。
        A continuous wavelet transform detection algorithm based on singularity information is proposed, which is used to detect shock wave signal. It is shown that prior information regarding the singularity of the signal to be detected is efficiently incorporated into the detection problem formulation. Based on the generalized likelihood ratio test, the theoretical analysis and experimental analysis of the detection performance of the algorithm are carried out.The theoretical analysis and simulation experiments show that the proposed detection algorithm can effectively improve the detection performance under low SNR.
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