首页|A modified stochastic model for LS+AR hybrid method and its application in polar motion short-term prediction

A modified stochastic model for LS+AR hybrid method and its application in polar motion short-term prediction

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  • 国家科技期刊平台
  • NETL
  • NSTL
  • 万方数据
  • 维普
Short-term(up to 30 days)predictions of Earth Rotation Parameters(ERPs)such as Polar Motion(PM:PMX and PMY)play an essential role in real-time applications related to high-precision reference frame conversion.Currently,least.squares(LS)+auto-regressive(AR)hybrid method is one of the main techniques of PM prediction.Besides,the weighted LS+AR hybrid method performs well for PM short-term prediction.However,the corresponding covariance information of LS fitting residuals deserves further exploration in the AR model.In this study,we have derived a modified stochastic model for the LS+AR hybrid method,namely the weighted LS+weighted AR hybrid method.By using the PM data products of IERS EOP 14 C04,the numerical results indicate that for PM short-term forecasting,the proposed weighted LS+weighted AR hybrid method shows an advantage over both the LS+AR hybrid method and the weighted LS+AR hybrid method.Compared to the mean absolute errors(MAEs)of PMX/PMY short-term prediction of the LS+AR hybrid method and the weighted LS+AR hybrid method,the weighted LS+weighted AR hybrid method shows average improvements of 6.61％/1 2.08％and 0.24％/11.65％,respectively.Besides,for the slopes of the linear regression lines fitted to the errors of each method,the growth of the prediction error of the proposed method is slower than that of the other two methods.

Stochastic modelLS+ARShort-term predictionThe earth rotation parameter(ERP)Observation model

Fei Ye、Yunbin Yuan

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State Key Laboratory of Geodesy and Earth's Dynamics,Innovation Academy for Precision Measurement Science and Technology,Chinese Academy of Sciences,Wuhan 430077,China

BeiDou High-precision Satellite Navigation and Location Service Hunan Engineering Research Center,Hunan Institute of Geomatics Sciences and Technology,Changsha 410007,China

Hunan Continuously Operating Reference Stations(HNCORS)Data Center,Hunan Institute of Geomatics Sciences and Technology,Changsha 410007,China

National Natural Science Foundation of China,ChinaHuBei Natural Science Fund,ChinaHuNan Natural Science Fund,ChinaHuNan Natural Science Fund,ChinaState Key Laboratory of Geodesy and Earth's Dynamics selfdeployment project,China

420040162020CFB3292023JJ605592023JJ60560S21L6101

2024

10.1016/j.geog.2023.05.005

大地测量与地球动力学(英文版)
中国地震局地震研究所

大地测量与地球动力学(英文版)

EI
影响因子：0.568
ISSN：1674-9847
年,卷(期)：2024.15(1)
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