一种改善微弱信号信噪比的小波变换消噪法

Method of Improving SNR of Weak Signal with Wavelet Transform

通过分析小波变换处理信号噪声的方法及其在微弱信号检测方面的不够完善之处,提出适合于极低信噪比条件下小波消噪法的信号检测原理和方法,即通过构造具有可调功能的阈值函数以及对小波分解系数处理方式的优化设计等方法,在强背景噪声中提取出微弱的信号特征信息,从而实现微弱信号的检测。最后通过Matlab仿真验证该方法的实验效果,理论和实验结果均表明此方法能较大幅度地改善信号比。这里阈值构造过程中充分考虑到了信噪比因素的影响,并对小波分解系数的处理也进行了合理优化,从而使得去噪效果有较大的改善。

By analyzing the faultiness of the wavelet method used in processing signal denoise and detection of weak signal. This thesis offers a suitable principle and method of detection weak signal with wavelet transform. By designing an adjustive threshold function and optimizing the mode of processing the wavelet coefficient, the characters of weak signal are obtained to realize weak signal＇s detection. In the end,the results are verified by Matlab program. It indicats that the method is useful in detecting the weak signal from strong noise background. It innovatively considers the factor of SNR in the design of threshold, and makes improvement on wavelet coefficient processing,thus the denoise effect is improved greatly.