系统工程与电子技术 ›› 2018, Vol. 40 ›› Issue (7): 1449-1456.doi: 10.3969/j.issn.1001-506X.2018.07.06

• 电子技术 • 上一篇    下一篇

α稳定分布噪声下水声线性调频信号的识别

孟庆松, 王彬, 邵高平   

  1. 信息工程大学信息工程学院,河南 郑州 450001
  • 出版日期:2018-06-26 发布日期:2018-06-26

Recognition of underwater acoustic linear frequency modulation signals in α-stable distribution noise

MENG Qingsong, WANG Bin, SHAO Gaoping   

  1. Information Engineering Institute, Information Engineering University, Zhengzhou 450001, China
  • Online:2018-06-26 Published:2018-06-26

摘要:

线性调频(linear frequency modulation,LFM)信号是一类重要的水声信号,在低信噪比(signal-to-noise ratio, SNR)和α稳定分布噪声条件下,对LFM信号进行识别会遇到一些困难。针对这个问题,在浅海水声多途脉冲噪声信道条件下,提出了适用于低SNR条件的LFM信号识别方法。该方法首先通过非线性变换抑制脉冲噪声,然后进行离散分数阶傅里叶变换(discrete fractional Fourier transform,DFRFT),通过分数阶傅里叶变换(fractionalFourier transform,FRFT)的结果构造出识别特征量,最后通过支持向量机(support vector machine,SVM)完成对LFM信号的识别。仿真实验结果表明,在混合信噪比(mixed signal-to-noise ratio,MSNR)为-15 dB时正确识别率高于94%。

Abstract:

The linear frequency modulation (LFM) signal is a kind of important underwater acoustic signal. Under the condition of low signal-to-noise ratio (SNR) and α-stable distributed noise, it is difficult to identify the LFM signal. To sdve this problem, an LFM signal recognition method suitable for low SNR conditions is proposed under shallow sea acoustic multi-channel with impulse noise. In this method, the impulsive noise is suppressed by nonlinear transformation, and then the discrete fractional Fourier transform (DFRFT) is carried out. The recognition feature is constructed by the result of fractional Fourier transform (FRFT). Finally, the identification of the LFM signal is completed by the support vector machine (SVM). The simulation results show that the correct recognition rate is higher than 94% when the mixed signal-to-noise ratio (MSNR) is -15 dB.