Study On Feature Extraction Of The Ship Radiated Noise Based On The Chaos Theory

The passive recognition technology of underwater targets is always a hot topic in the field of underwater signal processing. For a long time, scientists have been improving the recognition technology of underwater targets by variant methods. Although the performance of recognition has been improved, the key of the question has still remained unresolved. This is caused by the complexity of underwater target radiated noise and the variety condition of the sea.After studying the mechanism of the underwater targets radiated noise, we learned that the signals are related to the correspondent dynamics. While the nonlinear time series analysis methods offer the technologies to process the underlying dynamics of the signals in the phase space. The targets recognition can be reached by extracting the features of the reconstructed dynamics using nonlinear methods. In this paper, some work has been done to extract the features of the ship radiated noise signals on the basis of the nonlinear methods and chaos theory. The main contributions of the dissertation are as follows:1.Two parameters of delay reconstruction in phase space are explored. The optimum delay time is evaluated by the average mutual information method; this method is more precise than the autocorrelation method. The minimum embedding dimension can be determined by the false nearest neighbors method, and embedding dimension of determination component in noise condition can be determined precisely by this method which can avoid the phase space disturbance because of the higher embedding dimensions.2.Nonlinear local project noise reduction is studied on the basis of principal components analysis (PCA), the principle of this noise reduction is to approximate piecewise and linearly the dynamics and to process local principal components analysis. Contrast to the simple PCA, the filter performance of the nonlinear localproject noise reduction method has been improved greatly, it can recover the wave of the origin signal and trajectories of phase space even in low S/N ratio.3.Feature extraction of time series based on chaos theory is explored, which include the problem of temporal correlation in correlation dimension method, the robust method to evaluate the maximum Lyapunov exponents, the extraction ofgeneralised dimensions and the evaluation of h2 entropy of time series. It can belearned by analyzing the ship radiated noise signals using nonlinear methods that the ship radiated noise signals aren't rigid fractal signals, but there are positive maximum Lyapunov exponents, this indicates that the ship radiated noise signals are nonlinear. The extraction test to the different class signals tell us that the correlation dimension and generalised dimensions may effectively involve the class information of differentships, otherwise the h2 entropy is difficult to classify the targets.