基于小波变换的频谱检测算法分析

An Analysis of Spectrum Detection Algorithm Based on Wavelet Transformation

文章分析了认知无线电频谱检测中匹配滤波检测、能量检测、周期平稳过程特征检测的性能,指出了噪声对各自检测性能的影响,给出了一种基于小波变换的信号频谱检测算法,着重对含噪2FSK、2PSK信号进行分离仿真。仿真结果表明,该算法可以有效地进行信号的成分分离,降低了噪声的频谱检测的影响。

This article analyses the performance of matched filter detection, energy detection, as well as cycle stationary process feature detection concerning cognitive radio frequency spectrum detection. In addition, it points out the effect of noise on the above-mentioned performance and comes up with a kind of spectrum detection algorithm based on wavelet transformation, concentrating on the separation simulation of 2FSK, 2PSK signal with noise. It turns out that this algorithm contributes to the effective component separation of signals and the reduction of the noise effect on spectrum detection.