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基于Lyapunov指数的水下目标信号混沌特征提取 被引量:5

A New Method for Feature Extraction of Ship Signals
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摘要 以 Takens定理为基础 ,通过对几种不同类别舰船信号采用相空间重构 ,建立了混沌分析的数学模型 ,研究了它们的相空间轨迹结构并计算最大 Lyapunov指数。结果表明 ,不同类别的舰船信号具有不同的空间轨迹 ,且对应不同的最大 Lyapunov指数。这一结果为水下目标信号的检测与识别提供了新的理论和方法。 In feature extraction of ship signals, spectral lines are usually used as the feature to distinguish among different kinds of signals. In this paper, we present a new method for feature extraction and identification of ship signals. Such a method uses the Lyapunov exponent as the feature of ship signals. By means of Takens theorem for state space reconstruction, we studied the portraits of several types of ship signals and established their corresponding mathematical model in the form of Eq.(3). The maximum Lyapunov exponents of ship signals were calculated using this model by Eqs.(12) through (15). In the simulation, we chose four types of different ship signals as the sample data. The results as given in Fig. 3 and Tab. 2 show that there exist different portraits and different maximum Lyapunov exponents for different types of ship signals. Therefore, we concluded that the Lyapunov exponents can be used as a new feature of ship signals for detection and identification of ships.
出处 《西北工业大学学报》 EI CAS CSCD 北大核心 2002年第4期633-636,共4页 Journal of Northwestern Polytechnical University
基金 国防基金 (2 0 0 0 J5 .3.2 .HK0 30 7)
关键词 混沌 Takens定理 LYAPUNOV指数 特征提取 水下目标信号 信号检测 目标识别 水声信号处理 Takens theorem, Lyapunov exponents, feature extraction, ship signals
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