地球自转参数的LS+AR超短期预报方法

地球自转参数(ERP)是卫星精密定轨中联系天球坐标系与地球坐标系的必要参数,是国际GNSS服务组织(IGS)和国际GNSS监测评估系统(i GMAS)分析中心的重要产品。为了提高中国测绘科学研究院分析中心(CGS)的线性模型预报精度,本文研究了最小二乘(LS)和自回归模型(AR)组合的超短期预报最优方法;通过不同周期数据确定最佳预报时长,利用LS+AR模型进行超短期预报,并通过IGS和i GMAS与线性模型产品对比。结果表明:利用8 d(时段)数据进行超短期预报最优;LS+AR模型预报精度明显优于LS模型;LS+AR的超短期预报方法优于分析中心的线性预报方法;EOP的PMX和PMY分量利用时段数据预报、LOD利用天数据预报精度更高。本文超短期预报方法能够提高ERP预报精度,为IGS或i GMAS分析中心的ERP预报提供了一定的参考意义。

Ultra Short-term Forecasting of Earth Rotation Parameters Based on LS+AR

Earth rotation parameters (ERP) are integral parameters for transformation between the celestial coordinates and the terrestrial coordinates in satellite precise orbit determination, and are also important products for Intenational GNSS Service (IGS) and International GNSS Monitoring and Assessment System (IGMAS).To improve the prediction precision of the linear prediction model used by Chinese Academy of Surveying & Mapping (CGS), the best method of ultra short-term forecasting based on LS+AR is researched.The optimal data length is determined with the CGS data, and then the LS+AR is used to predict the ultrshort term ERP.The results are compared to that of the IGS and iGMAS and show that the optimal data length is eight days (sessions).The prediction precision of LS+AR is much better than that of LS, and also better than the linear model used by CGS.The results also show that the x and y direction prediction of ERP is better with the session's data than the day's data, while the LOD is better with the day's data than the session's data.The LS+AR ultrashort term prediction is a good method to predict the ERP for IGS and iGMAS analysis centers.