Dissertation > Industrial Technology > Radio electronics, telecommunications technology > Communicate > Communication theory > Information Theory > Signal detection and estimation

Signal Detecting Based on Chaos and Fractal

Author YuQiuXing
Tutor LiZhiShun
School Northwestern Polytechnical University
Course Signal and Information Processing
Keywords Withdrawn chaos Fractal Fractal dimension Detect Neyman - Pearson guidelines Ship Radiated Noise Echo State Space Reconstruction Wavelet Analysis Probability of false alarm Probability of detection
CLC TN911.23
Type Master's thesis
Year 2001
Downloads 476
Quotes 7
Download Dissertation

This paper focuses on the theme of signal detection , focusing on Chaos and Fractals signal processing method and its applications in underwater acoustic signal processing , and Chaos and fractal signal processing method used in passive signal detection and active signal , respectively computer simulation , and achieved good results . The main work of this paper are as follows: 1 to study the chaotic characteristics of underwater acoustic signals . Through theoretical analysis and simulation results show that underwater acoustic signal to a certain extent on the character of chaos . 2 ship noise power spectrum has the characteristics of the decline in a certain number of decibels per octave , thus indicating that the ship noise is 1 / f signal ; same time , theoretical analysis, the ship noise is a fractional Brownian motion conclusion. The proposed detection method based on state space reconstruction , under the background of white noise of ship radiated noise detection , and achieved good results . Proposed signal detection method based on wavelet analysis , white noise background ship radiated noise detection , and its detection is better than the traditional energy detection method . 5, the signal detection method based on wavelet analysis applied to the detection of the echo signal in the 1 / f noise context and compared with the conventional matched filter detection effect .

Related Dissertations
More Dissertations