基于Hilbert-Huang变换的水声信号特征提取及分类技术

Feature extraction and classification of underwater signals based on Hilbert-Huang transform

水下目标噪声信号是一种典型的非线性非平稳随机信号,Hilbert-Huang变换较传统方法在处理此类信号时具有很大优势,据此本文提出了一种基于Hilbert-Huang变换的水下目标噪声特征提取方法．本文将环境噪声当作一类目标,利用上述方法对涉及两种航行船舶、海洋生物和海洋环境噪声的四类目标信号的特征进行了详细分析,最后对各类目标噪声信号进行了分类识别实验．实验结果表明基于Hilbert-Huang变换提取的特征对各类目标具有较好的可分性,达到了较高的识别率．

Noise radiated from underwater targets is a typical nonlinear and non-stationary signal. Hilbert-Huang Transform is a good method of analyzing this kind of signals compared to other traditional methods. Based on this method, a new feature extraction method is proposed in this paper. The targets are divided into four types： cargo ship, fishing boat, maxine life and sea noise, and their characteristics are described. Experiments on actual noises of underwater targets are carried out, and the results illustrate the method is effective.