【摘要】 为降低原子钟频差的噪声,根据其数据非线性非平稳的特征,将整体经验模态分解用于原子钟频差去噪算法。首先将原子钟频差数据叠加一定强度的白噪声;然后进行经验模态分解,如此重复多次;最后将各分量叠加求平均得到去噪的原子钟频差序列。从时域和频域上分别分析了该算法的去噪效果,并与小波阈值去噪算法进行了比较。结果表明,该算法有效地去除了原子钟频差数据序列中的噪声,将方差由小波算法的2.707%降为0.7263%,数据变得更加平稳。更多还原

【Abstract】 To reduce the noise in the clock frequency, since the hydrogen atomic clock frequency differences are nonlinear and non-stationary with time, the denoise algorithm based on ensemble empirical mode decomposition is put forward.Firstly, the clock frequency differences are added a certain intensity noise; then decompose the differences with the EMD algorithm, repeat this step many times; finally, calculate the mean of the same components to get the denoise clock frequency differences. Compared with the wavelet algorithm in the time domain and frequency domain, the result shows that, the algorithm put forward in this paper is better than the wavelet algorithm in the denoise of the clock frequency differences,the data variance is 0.7263% which is 2.707% in the wavelet algorithm, the data become more stable.更多还原