【摘 要】
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Daily position time series from 2001 to 2013 at 13 stations in Southern California integrated GPS Network (SCIGN) are used to study the optimal noise model for
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Daily position time series from 2001 to 2013 at 13 stations in Southern California integrated GPS Network (SCIGN) are used to study the optimal noise model for position time series of regional GNSS network,and the effect of the noise model to the estimation of station velocity is also analyzed.In this paper,the position time series is preprocessed by orthogonal polynomial least square fitting and principal component analysis,and then the residual time series is processed by CATS software to determine the optimal noise model.The results show that the station velocity and the uncertainty value which are estimated under the optimal noise model determined by the method proposed in this paper have a strong consistency with the products from SOPAC.
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