广义S变换域有色噪声与信号识别方法

RECOGNITION OF SIGNALS FROM COLORED NOISE BACKGROUND IN GENERALIZED S-TRANSFORMATION DOMAIN

为研究广义S变换域有色噪声与信号识别问题 ,首先推导白噪声在S变换和广义S变换下平均功率谱的统计规律 ,白噪声的平均功率谱与频率呈线性关系 .然后从理论上定性分析一般的有色噪声功率谱的分布特性 ,得出在广义S变换域有色噪声的功率谱服从自由度为 2的 χ2 分布的规律 ,并用MonteCarle方法进行了验证 .在上述工作基础上 ,本文提出了利用噪声和有效信号统计特性的差别 ,在广义S变换域中区分噪声和信号的方法 ,并用模型数据证明了方法的有效性 .

We study how to distinguish signals from colored noise in the S-transform (ST) and generalized S-transform (GST) domain. First, the mean ST and GST power spectra of white noise are derived. The result shows that they are related linearly with frequency. Then the local GST power spectrum of colored noise is qualitatively analyzed. It is concluded that the local GST spectrum of colored noise follows chi-square distribution with two degree of freedom. These conclusions are verified by Monte Carle simulation. Based on the above results, a method to distinguish signals from colored noise is proposed, and its effectiveness is proved by synthetic data.