舰船辐射噪声混沌特征提取方法研究

Research on Chaotic Feature Extraction of Ship Radiated Noise

研究舰船辐射噪声信号影响目标识别,针对传统子空间降算法只适用于多通道信号处理,为了清楚识别目标,提出多次迭代降噪的思想,并根据定义的信噪比改善量控制迭代次数。用相空间重构进行特征提取,为了降低特征维数,引入K-L变换进行特征压缩,提出一个基于子空间降噪理论与相空间重构以及K-L变换相结合的完整的舰船辐射噪声特征提取方法,进行计算机仿真,结果表明对舰船辐射噪声特征有效提取和分类识别很有效,证明方法对三类目标舰船噪声信号具有较好的分类效果。

An improved subspace noise reduction method is proposed,for the conventional subspace noise reduction method is merely adapted to multi-signals,and the phase space reconstruction is combined to transform the single signal to multi-signal.An advanced multiple iterative noise reduction algorithm is presented,which takes the defined SNR improvement as an iterative controller.K-L transform is cited to reduce the feature dimension.This paper forms a whole ship radiated noise feature extraction system based on subspace noise reduction theory,phase space reconstruction and K-L transform.Simulation results show that the method has good effect in classifying three types of ship.