引用本文: 马俊, 姜卫平, 邓连生, 周伯烨. GPS坐标时间序列噪声估计及相关性分析[J]. 武汉大学学报 ( 信息科学版), 2018, 43(10): 1451-1457.
MA Jun, JIANG Weiping, DENG Liansheng, ZHOU Boye. Estimation Method and Correlation Analysis for Noise in GPS Coordinate Time Series[J]. Geomatics and Information Science of Wuhan University, 2018, 43(10): 1451-1457.
 Citation: MA Jun, JIANG Weiping, DENG Liansheng, ZHOU Boye. Estimation Method and Correlation Analysis for Noise in GPS Coordinate Time Series[J]. Geomatics and Information Science of Wuhan University, 2018, 43(10): 1451-1457.

## Estimation Method and Correlation Analysis for Noise in GPS Coordinate Time Series

• 摘要: 比较分析了极大似然估计法、最小二乘方差分量估计法以及最小范数二次无偏估计法对GPS站坐标时间序列噪声的估计效果，确定最小范数二次无偏估计法为最优的噪声方差估计方法。在此基础上对中国及其周边区域20个IGS站坐标时间序列中各方向噪声方差进行一元线性回归分析。结果表明，中国及其周边区域IGS站不同方向的噪声间具有中等强度以上的相关性，其中N方向闪烁噪声与其他方向闪烁噪声的相关性要强于白噪声。水平方向的噪声振幅能够解释垂直方向噪声振幅变化的40%~60%，而N方向噪声振幅能够解释E方向噪声振幅变化的60%~80%，获得的线性回归方程具有使用价值。

Abstract: This paper firstly compares and analyzes the effect of maximum like lihood estimation (MLE) and least square variance estimation (LS-VCE) and minimum norm quadratic unbiased estimation (MINQUE) in the variance component estimation of GPS coordinate time series noise. After determining the minimum norm of two unbiased estimation method for the optimal estimation of noise variance, the correlations between the noises in each direction are analyzed by means of unitary linear regression, and the linear regression equations are determined.Experimental results show that, compared with the least squares variance component estimation method and maximum likelihood estimation method, MINQUE has a better estimation effect for the noise variances of GPS coordinate time series.In addition, the influence of noise on the estimation of motion parameters of the station can be reduced by using long span time series.Moreover, the same kind of noise in GPS coordinate time series of each direction has more significant correlation and the correlation between flicker noise in north and other directional flicker noises are better than that of white noises. The 40%-60% of the variance of the vertical noise can be explained by the noise variance in the horizontal direction, and north noise variance can explain the 60%-80% of change of the noise variance in east.The obtained linear regression equation has practical value.

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