The Using Of Chaos Theory In The Underwater Target Recognition

Chaos is one of the most important scientific discoveries in the 20th century and it has been regarded as the third revolution in the physics after the theory of relativity and the quantum mechanics. The chaos theory is one of the most challenging research topics in the world and its application has reached a broader area. Underwater target signal detection and feature extraction have a very important effect on the development of modern underwater weapon. It is the focus of underwater acoustics that chaos theory is used in detecting underwater signals, feature extraction, target recognition and classification by means of calculating chaotic characteristic parameters of underwater acoustic signals.With the underwater target recognition and classification as the main topic of this dissertation, chaotic signal processing methods are applied to the feature extraction and the target recognition of ship-radiated noise. The state space reconstruction theory is discussed systematically. The main methods of state space reconstruction now are analysis compared. Two new methods of state space reconstruction are proposed based on the Higher Order Statistics. The definition of Lyapunov exponent , correlation dimensions , h2 entropy and natural measure are introduced and the estimate methods of these chaotic exponents are studied. The simulation of feature extraction for two chaotic system such as Henon system and Lorenz system has been down. The four chaotic exponents for two different types of ships are calculated and there ability of classification is studied. The classification experiment for two different types of ships is down which base on correlation dimensions and natural measure by using BP classifier. The result of the experiment show that the correlation dimensions and natural measure accomplished the classification and the classification rate is higher.