为提高 GPS 数据的精确度和可靠性，采用最小二乘平差原理、最小二乘平差的3倍单位权中误差限差准则和稳健估计粗差探测的四分位距(IQR)准则，对数据进行粗差探测、剔除、分类处理与比较，并基于 MATLAB 平台采用时间序列拟合模型与谱分析法对我国国际 GNSS 服务组织(IGS)站的高程分量数据进行研究。通过对北京房山站高程数据的研究可以看出，GPS 点位高程分量的时间序列的残差序列近似于正弦函数，周期近似为1年，振幅为0.03，高程分量数据不仅存在很明显的线性趋势，而且存在较明显的周期特性。表明最小二乘原理、误差限差和 IQR 准则可以很好地体现高程数据的线性特征、周期特征及残差谱特征。%In order to improve the accuracy and reliability of GPS data, a method based on the least squares adjustment principle, the least squares adjustment with three times the unit weight error tolerance criteria and robust estimation of gross error detection Inter Quartile Range(IQR) criteria is proposed to detect, eliminate, classify and compare the data in gross error. And time series fitting model and spectral analysis are used to study the elevation components data of the International GNSS Service(IGS) station in the MATLAB platform. By studying the elevation data of Beijing Fangshan station, we can see that the residuals time series of GPS point elevation component are similar to the sine function, of which the period is approximately 1 year, with an amplitude of 0.03. Elevation components from the image data analysis present an obvious linearity, as well as a periodicity, which demonstrates that the principle of least squares, error tolerance and IQR criteria can well reflect the linearity, periodicity and residual spectral features of the elevation data.
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