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基于极限环的舰船噪声信号非线性特征分析及提取

Nonlinear feature analysis and extraction of ship noise signal based on limit cycle

  • 摘要: 特征分析及提取是目标分类识别的重要环节.首先应用非线性分析方法分析了舰船噪声的极限环现象,结果表明振动噪声作为舰船噪声的主要成份,其极限环在相空间上存在倍周期或混沌行为.其次,利用分形维数和分布密度比来描绘舰船噪声在相平面上极限环的奇异性和空间形状,并给出了一种新的分维数计算算法.最后,以此作为舰船目标的特征参数送入神经网络分类器用于分类识别水面和水下两大类目标.实验结果表明。从噪声极限环中提取的非线性特征能较准确地区分我们现有的水面和水下两大类目标.。

     

    Abstract: Feature analysis and extraction is a key issue of target classification, in this paper, at first, the nonlinear analysis method is used for studying the limit cycle phenomenon of ship noise,and the result indicates that the period-doubling or chaos would happened with limit cycle of vibration noise in phase space,which is the main component of shop noise. Second,the fractal dimension and distribution density ration are used for calculating the strangeness and shape of limit cycle,and a new algorithm of fractal dimension calculation is proposed,At last,the fractal dimension and distribution density ration are chosen as feataure parameters of ship noise for calssifying sea ship and underasea ship by using neural network classifier,The results of experiment on our ship noises show that the nonlinear features based on ship noise limit cycle is effective in classification of two classes of ship targets,The research of this paper gives a novel effective method for feature extraction of ship noise signals.

     

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