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中文摘要：
GPS位置时间序列中经常会出现信息中断,造成数据不连续,进而导致测站速度及其不确定度的估计有偏。因此,时间序列中断探测是动态大地测量数据处理的重要内容。在基于t-检验的序贯格局转换分析法（sequential t-test analysis of regime shifts,STARS）算法的基础上,顾及GPS位置时间序列的噪声特性,提出了一种考虑有色噪声的STARS算法（COL-STARS）。该算法首先利用一阶自回归模型（auto-regressive,AR（1））模型进行噪声＂白化＂,然后再进行数据中断探测。经模拟数据和实测数据分析,改进后的COLSTARS算法在一定程度上降低了中断探测的误判,能提高GPS位置时间序列中断探测的准确率。同时,也对STARS算法的参数设置以及滤波对中断探测的影响分别进行了讨论。
英文摘要：
Offsets in GPS position time series often lead discontinuities in deformation analysis.The estimation of geodetic station velocities and their uncertainties will be biased if the offsets are not modeled.The detection and correction of offsets are fundamental steps in pre-processing of GPS position time series in dynamic geodetic studies.In this paper,based on the Sequential t-Test Analysis of Regime Shifts（STARS）algorithm,we propose a colored modified method called COL-STARS to detect offsets considering the noise characteristics of GPS position time series.We first use an AR（1）model to whiten the original GPS position time series,then the STARS method is applied to detect the offsets.Simulated and real examples show that the COL-STARS algorithm can reduce the ratio of missidentification of the offsets somewhat,and can be used for offset detection and correction.The impact of parameters setting and filtering on the offsets detection is also discussed.
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