水下目标辐射噪声中的谐波分量包含了反映目标自身本质特性的信息，能否有效提取目标谐波特征关系到目标识别的效果。论文基于目标辐射噪声的一般数理模型，利用最大似然估计和卡尔曼滤波理论，提出一种水下目标辐射噪声谐波特征的提取与分析算法，估计得到了谐波的瞬时基频；然后利用卡尔曼滤波器跟踪瞬时基频的时变特性，实现对基频的精确跟踪和估计；并提取各阶谐波的振幅，得到目标的谐波特征；最后结合仿真信号与实测数据进行对比，验证了谐波特征提取算法估计基频和提取谐波信息的可行性。
The harmonic components for radiated noise of underwater-target contain information reflecting nature of target itself, and extracting effectively target harmonic is related to result of target recognition. By combining likelihood estimation method and Kalman filtering tracking approach, a new feature extraction algorithm was developed to extract the harmonic feature from the underwater noise radiated. The likelihood estimation method gives an estimation of the instant fundamental frequency, while Kalman filter is adopted to capture the time varying structure. The fundamental frequency tracks are then used to extract the amplitudes of harmonics and obtain harmonic feature of target. Based on the comparison of simulated signal and the measured data, feasibility is verified of harmonic feature extraction algorithm estimating undamental frequency and extracting harmonic information.
2017,39(9): 133-137 收稿日期：2016-11-14
DOI：10.3404/j.issn.1672-7649.2017.09.026
分类号：TP391
基金项目：国家自然科学基金资助项目（61271444）
作者简介：梁巍(1984-),男,硕士研究生,助理工程师,研究方向为水声工程
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