基于TWSTFT进行钟差预报方法分析

Numerical Prediction Methods Analysis of the Clock Difference Based on TWSTFT Data

用多项式拟合、频谱分析、改进的AR模型3种方法对由TWSTFT(卫星双向时间频率传递)得出的钟差时间序列进行了拟合和预报分析。为了抵制钟差时间序列中异常值的影响,引入了“抗差等价权”。利用TWSTFT得到的一天的钟差,按不同采样率、不同时间跨度进行计算分析,结果表明:抗差估计的预报精度明显高于最小二乘估计;平滑值的预报精度高于采样值;由于钟差时间序列中有明显的周期变化,多项式进行钟差预报的精度不可靠;用谱分析进行钟差预报的精度不高,但可以发现钟差时间序列中的主要周期变化;改进的AR模型预报精度最高,预报RMS在1 ns左右。

Three functional models（polynomial, spectral analysis, and modified AR model） are fitted and compared in fitting and predicting the clock differences based on the data series derived from TWSTFT （two - way satellite time and frequency transfer）. A robust equivalent weight is applied, which controls the significant of outlying observations. By calculation and analysis using one day clock differences, which is in different sampling and different span, following useful conclusions are drawn： （ 1 ） The prediction precision of robust estimation is better than that of IS. （2）The prediction precision calculated from smoothed observations is higher than that calculated from sampling observations. （3） As a count of the obvious period variations in the time series, the prediction result of polynomial model is uncertainty. The prediction precision of spectral analysis is very low, but the main period variations can be determined. The prediction RMS is 1 ns or so, when modified AR model is used.