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低信噪比下基于多元变分模态分解的水下蛙人特征提取

Acoustic feature extraction of divers based on multivariate variational mode decomposition with low signal-to-noise ratio

  • 摘要: 为提高低信噪比下对蛙人辐射噪声的提取能力, 提出了一种矢量多通道信号的水下蛙人辐射噪声特征提取方法。首先针对矢量多通道信号使用多元变分模态分解, 得到固有模态函数。然后选取能量最高的模态函数组作为研究对象, 计算该模态函数组互谱后的加权排列熵。最后提取加权排列熵频谱的蛙人特征量。海试结果表明, 本方法可在无需先验信息情况下, 提取由矢量水听器采集的蛙人信号特征, 在检测率为80%的情况下抗噪能力较传统算法提升了10 dB。

     

    Abstract: Aiming at improving the ability to extract feature of divers under low signal-noise-ratio, a method is proposed to extract acoustic feature of divers for vector multi-channel signals. Firstly, the multivariate variational mode decomposition is used for vector multi-channel signals to obtain intrinsic mode functions. Then, the intrinsic mode function with the highest energy is selected to calculate the cross-spectrum and its weighted permutation entropy. At last, the feature of weighted permutation entropy spectrum is extracted by the fast Fourier transform. The results of sea trial show that, the proposed method can effectively extract feature of divers with vector hydrophone without prior information, and the noise immunity is improved by 10 dB compared with the traditional algorithm with 80% detection rate.

     

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