时间跨度对GPS坐标序列噪声模型及速度估计影响分析

选取全球范围内72个基准站的坐标序列,采用改进的赤池信息量准则、贝叶斯信息量准则对不同噪声模型组合进行噪声分析,得到基准站坐标序列的最优噪声模型及速度参数,探讨时间序列跨度对噪声模型及速度估计的影响。结果表明,基准站坐标序列噪声模型不能由单一的噪声模型表述,其呈现出多样性特征,主要表现为幂律噪声、高斯马尔科夫噪声、闪烁噪声+白噪声特征,且三坐标分量表现出不同的噪声特性;随着时间跨度的增加,坐标时间序列的最优噪声模型、GPS站速度及其不确定度逐渐由发散趋于收敛,随机游走噪声模型的比重有所增加。结果表明10 a以上的时间跨度是较为理想的噪声模型估计尺度。

Investigation of time span on GPS time series noise model and velocity estimation

72 IGS core stations range from 7 to 20 years long span were selected to make perform analysis on GPS noise model and uncertainties of the velocity. An improved AIC / BIC model estimation criteria was developed to evaluate different combinations of noise model, to establish the best noise model of GPS time series and gain the aureate velocity parameters. Results show that the noise model of GPS time series cannot be described as simple noise, tend to showing diversity, and can be best described by PL, GGM, FN+WN model, the ENU components exhibit different noise characteristics. The span of coordinate time series affects the determination of an optimal noise model. As the time span increases, the noise model tends to be convergent and the velocity uncertainty becomes steady. It is proposed to use time series longer than 10 years to reduce the effect of noise on velocity and its uncertainty estimation. Besides, the proportion of random walk noise is proved to increase as time span increases, indicating that it is difficult to detect random walk noise with short time series.