基于小波变换的子带自适应滤波算法及仿真

Algorithm for Weak Signal Detection with Adaptive Matched Filter Based on Wavelet Transform

因为噪声总是影响信号检测的结果,所以低信噪比下的信号检测是目前检测领域的热点,而强噪声背景下微弱信号的提取又是信号检测的难点。自适应滤波器为检测信号提供了一种简单、实用的方法。可以在微弱信号的条件下,通过测量和学习,实现对微弱信号的最佳拟合。提出基于自适应小波变换的心电信号的检测,利用小波变换的子带编码理论,通过在多个子带权值的自适应匹配,合成后拟合微弱信号。仿真结果表明,该方法可进一步改善信号的检测能力,在检测微弱信号的特征和改善信噪比方面是一种十分有效的方法。

The demand for detection of objects with low probability of observation is increasingly needed. The reason is that noises always badly affect measured results. The method of signal detection in low signal to noise ratio （SNR） is widely concerned. To detect the weak signals buried in noise is a fundamental and important problem. Adaptive filter provides a kind of simple and applied method for processing weak signals in noise. It can attain a best approach of the weak signals through measuring and learning. We adopt the sub-band coded theory of WT and synthesis post-combination weak signal adaptation matching of multi sub-band＇s weights. An algorithm for ECG signal detection with wavelet Transform based on adaptive matched filter is proposed. The simulation results show that this method can further improve the detection capability. The algorithm is a quite effective method for the extraction features of weak signal and improving the ratio of signal to noise