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Improved LS+MAR hybrid method to ut1-utC ultra-short-term prediction by using first-order-difference ut1-utC

Geodesy and Geodynamics 2024年第4期15卷 379-385页

作者： Fei Ye Yunbin Yuan BeiDou High-precision Satellite Navigation and Location Service Hunan Engineering Research Center Hunan Institute of Geomatics Sciences and TechnologyChangsha410007China State Key Laboratory of Geodesy and Earth's Dynamics Innovation Academy for Precision Measurement Science and TechnologyChinese Academy of SciencesWuhan430077China HNCORS Data Center Hunan Institute of Geomatics Sciences and TechnologyChangsha 410007China

Accurate ultra-short-term prediction of the Earth rotation parameters(ERP)holds paramount impor-tance for real-time applications,particularly in reference frame *** them,diurnal rota-tion(ut1-utC)which cannot be directly estimated through Global Navigation Satellite System(GNSS)techniques,significantly affects the rapid and ultra-rapid orbit determination of GNsS ***-ently,the traditional LS(least squares)+AR(autoregressive)and LS+MAR(multivariate autoregressive)hybrid methods stand as primary approaches for ut1-utC ultra-short-term predictions(1-10 days).The LS+MAR hybrid method relies on the ut1-utC and LOD(length of day)***,the correlation between LOD and first-order-difference ut1-utC is stronger than that between LOD and *** light of this,and with the aid of the first-order-difference ut1-utC,we propose an enhanced LS+MAR hybrid method to ut1-utC ultra-short-term *** using the ut1-utC and LOD data series of the IERS(International Earth Rotation and Reference Systems Service)EOP 14 C04 product,we conducted a thorough analysis and evaluation of the improved method's prediction performance compared to the traditional LS+AR and LS+MAR hybrid *** to the numerical results over more than 210 days,they demonstrate that,when considering the correlation information between the LoD and the first-order-difference ut1-utC,the mean absolute errors(MAEs)of the improved LS+MAR hybrid method range from 21 to 934μs in 1-10 days *** comparison to the traditional LS+AR hybrid method,the MAEs show a reduction of 7-53μs in 1-10 days predictions,with corresponding improvement percentages ranging from 1 to 28%.Similarly,when compared to the traditional LS+MAR hybrid method,the MAEs have a reduction of 5-42μs in 1-10 days predictions,with corresponding improvement percentages ranging from 4-20%.Additionally,when aided by GNSS-derived LOD data series,the MAEs of improved LS+MAR hybrid method experience further

关键词： ut1-utcultra-short-termprediction Rapidandultra-rapidproducts LS+AR and LS+MAR Correlation First-order-differenceut1-utC

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