Signal Detecting Based On Chaos And Fractal

In this dissertation, research works focus on that the method of chaotic and fractal signal processing and its application in underwater acoustic signal processing, which mainly include detecting passive signal and detecting active signal0 Through the computer simulation , satisfactory experimental results are obtained. The primary endeavor and contributions of this dissertation are as follows: (1) The chaotic property of acoustic signals has been analyzed Both the theory analysis and the experimental results show that the acoustic signals are chaotic. (2) Ship noise has been proved to be 1/f signal and to be a kind of Fractal Brown Motion. (3) A detection method based on state space reconstruction has been developed, by which three kinds of ship noise embedded in zero-mean and unit-variance additive stationary white Gaussian noise can be detected and good performance has been obtained. (4) A wavelet-based approach has been proposed to detect three kinds of ship noise embedded in zero-mean and unit-variance additive stationary white Gaussian noise and the performance is better than traditional energy detector. (5) The wavelet-based approach has been utilized to detect active acoustic signals in the background of 1/f signal and the results of simulation show that this approach is superior to the tradi tional matching fi lter.