中文摘要：

针对传统时频分析方法在水下目标特征提取时的局限性，采用一种基于经验模态分解和 Wigner-Ville 分布（ Wigner-Ville distribution，WVD）的提取水下小目标亮点特征的新方法。该方法可以将多分量信号分解为一组单分量信号进行分析，不仅可以有效地抑制WVD分布中多分量信号所产生的严重的交叉项干扰，而且解决了噪声对HHT谱产生波动的影响，通过仿真分析和实验数据的处理验证了该方法的有效性。对三类目标模型的回波进行了特征提取，并分析了各类模型回波的不同特点。其中，规则雷的回波以镜反射波为主；不规则雷的亮点结构相互叠加致使频带范围变宽；假雷的回波由于是多个信号的非线性叠加，使得到的时频特性分布较广、比较散乱。

英文摘要：

To deal with the limitations in feature extraction of an underwater target based on traditional time-frequen-cy analytical methods, a new method based on empirical mode decomposition and Wigner-Ville distribution ( WVD) is adopted to extract the highlight features of small underwater targets. Multiple-component signal can be decomposed into a collection of single component signals, which can not only restrain the severe cross-term interfer-ence in WVD method caused by multiple-component signals, but also solve the problem that HHT spectrum can be influenced by noise. Simulation analysis and experiment results have affirmed the effectivity of the method. Echo waves of three different target models are analyzed by feature extraction, and each gets a different conclusion. Echo waves of the regular mine models are mainly composed of specular reflection. Echo waves'superposition of the irreg-ular mine models widens the frequency band. And echo waves of false target are caused by several signals'nonlinear superposition, which widen the time-frequency feature distribution and make the highlight extraction harder.