强噪声下小波包自适应算法的研究

Adaptive Filtering Algorithm with Wave Packet for Low SNR Signal Detection

低信噪比下信号检测一直备受关注.已有的方法多集中于FFT变换和自适应滤波算法的结合,尤其是变步长因子的改进上.随着小波、小波包的时频分析能力和变分辨特性日趋完善,小波逐渐成为信号处理的首选.本文算法先把信号小波包分解,然后自适应滤波运用于分解后的每个子波,最后小波包信号重构,并以罗兰-C信号为例验证其有效性.

Low SNR signal detection is a focus of concern.The proposed methods have been more focused on the combination of the FFT and adaptive filtering algorithm,in particular,the improvement of the variable step-size factor for adaptive filtering algorithm.With the advancement of its ability to time-frequency analysis and to multi-scale analysis,the method using wavelet and wavelet packet has gradually becoming the preferred signal processing.This algorithm first decomposes signal with wavelet packet,and then applies adaptive filtering to the decomposed signal.Finally,the filtered signals are reconstructed with wavelet packet,and Loran-C signal as an example verifying this algorithm＇s effectiveness.