毕业论文

基于小波变换的微弱信号检测技术研究

学生姓名： 学号：

学 院：

专 业：

指导教师：

2012年 6月

基于小波变换的微弱信号检测技术研究

摘要：

微弱信号检测的目的是要提取需要检测到的微弱信息，利用小波分析方法遏制噪声放大信号以达到检测微弱信号的目的。

小波分析理论是一种新兴的信号处理理论，它在时间上和频率上都有很好的局部性，它可以将信号的高频成分和低频成分分开。由于噪声信号多存在于高频部分，从而实现降噪目的。小波分析理论[1]已经成为信号降噪中的一种重要的工具。利用小波方法降噪，是小波分析应用于实际的重要方面。

本文是在假设噪声为高斯白噪声的前提下，根据小波分解和重构法，实现微弱信号的降噪处理。文中介绍了小波降噪的基本原理及基本步骤，硬阈值和软阈值降噪方法，描述了4种阈值形式及其选取规则。小波降噪的关键是如何选择阈值和如何利用阈值来处理小波系数，通过对小波阈值化降噪的原理介绍,运用MATLAB 中的小波工具箱，对一个含噪信号进行阈值降噪。通过对几种降噪方法比对分析和基于MATLAB信号降噪的仿真实验，验证小波降噪的优越性。其中的阈值降噪的方法是一种实现简单、效果较好的小波降噪方法。

关键词：微弱信号，小波分析 ，MATLAB工具 ，降噪处理，阈值

Weak Signal Detection Based On Wavelet Analysis

Abstract:

The purpose of the weak signal detection is to extract need to detect weak to information, using the wavelet analysis method contain noise amplification signal in order to achieve the purpose of the weak signal detection.

Wavelet analysis theory is a new signal process and it has good localization in both time and frequency, which makes the wavelet analysis suitable for the time -frequency analysis. It can be divided high frequence and low frequence .Because of the noised signal mostly exist to the high frequence,thus it shows a prominence effect in denoise. Wavelet analysis theory has become an important tool in the signal de-noising. Using wavelet methods in de-noising, is an important aspect in the application of wavelet analysis.

On the consumption that the noise is the Gaussion white noise ,the noise has been excluded from the corrupted signal relying on the wavelet transform and reconstruction.This paper introduces the principle of wavelet de-noising and process of wavelet de-noising,the de-noising method of the soft or hard thresholding .This paper describe four kinds of threshold rules and the choices of thresholding rule.The key of wavelet de-noising is how to choose a threshold and how to use thresholds to deal with wavelet c