【摘要】 针对舰船辐射噪声特征存在非线性、非平稳的时变特点，导致特征识别难度较高的问题，本文提出一种基于贝叶斯的舰船辐射噪声特征识别方法。利用Dopplerlet变换方法，选取高斯函数作为基函数，变换舰船辐射声场信号。利用VMD算法获取搜寻约束变分模型的最优解，将完成变换的舰船辐射信号，分解为多个IMF分量，提取舰船辐射噪声特征。利用所提取的舰船辐射噪声特征构建特征样本集，通过贝叶斯网络计算样本集内各样本的状态概率，识别舰船辐射噪声特征。结果表明，该方法有效识别水面舰船、水下低速运动舰船等不同类型舰船的辐射噪声，适用于舰船目标识别应用中。更多还原

【Abstract】 Aiming at the problem that the characteristics of ship radiated noise have nonlinear and non-stationary timevarying characteristics, which leads to high difficulty in feature recognition, this paper proposes a method of ship radiated noise feature recognition based on Bayesian. The Doppler transform method is used to transform the ship radiated sound field signal by selecting Gaussian function as the basis function. The VMD algorithm is used to obtain the optimal solution of the search constrained variational model. The transformed ship radiation signal is decomposed into multiple IMF components to extract the characteristics of ship radiation noise. The feature sample set is constructed by using the extracted ship radiated noise features, and the state probability of each sample in the sample set is calculated by Bayesian network to identify the ship radiated noise features. The results show that this method can effectively identify the radiated noise of different types of ships, such as surface ships and underwater low-speed moving ships, and is suitable for ship target recognition applications.更多还原