| 地球自转参数的RFFLS短期预报算法研究 |
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| 引用本文： | 韩恒星,党亚民,许长辉.地球自转参数的RFFLS短期预报算法研究[J].测绘通报,2017(9). |
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| 作者姓名： | 韩恒星 党亚民 许长辉 |
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| 作者单位： | 1. 山东科技大学,山东青岛 266590;中国测绘科学研究院,北京100830;2. 中国测绘科学研究院,北京,100830 |
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| 基金项目： | 国家自然科学基金，国家重点研发计划，公益性行业专项，国家基础测绘科技项目，中国第二代卫星导航系统重大专项 |
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| 摘 要： | 地球自转参数(ERP)是实现地心天球坐标系(geocentric celestial reference system,GCRS)与国际地球坐标系(international terrestrial reference system,ITRS)相互转换的必要参数,是国际GNSS服务组织(IGS)和国际GNSS监测评估系统(iGMAS)分析中心的重要产品。本文针对最小二乘地球自转参数预测算法会造成数据饱和以及新旧数据在数据处理及预报中被同等对待等问题,将遗忘因子引入最小二乘预测算法,进而提高ERP预报精度。遗忘因子递推最小二乘算法能防止数据饱和,降低旧数据的影响,加强新数据的作用,降低在求解拟合参数时出现秩亏矩阵求逆的几率,提高预报精度。本文详细推导了遗忘因子递推最小二乘表达式,探究了最佳遗忘因子,并通过ERP试验将该方法和原最小二乘的试验结果及LS-AR模型的预报结果作对比,发现仅用遗忘因子最小二乘模型预测就可以达到与LS-AR组合模型预测相当的精度。
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| 关 键 词： | 地球自转参数 预报 遗忘因子 递推最小二乘 |
Short-term Forecasting of Earth Rotation Paarmeter Based on Forge tting Factor Recursive Least Squares |
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| HAN Hengxing,DANG Yamin,XU Changhui.Short-term Forecasting of Earth Rotation Paarmeter Based on Forge tting Factor Recursive Least Squares[J].Bulletin of Surveying and Mapping,2017(9). |
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| Authors: | HAN Hengxing DANG Yamin XU Changhui |
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| Abstract: | The earth's rotation parameters(ERP)is an essential parameter for the conversion between the geocentric celestial reference system( GCRS)and the international terrestrial reference system ( ITRS)I.t is the important products of the International GNSS Service Organization( IGS) and the International GNSS Monitoring and Evaluation System Analysis Center ( iGMAS)I.n this paper,the least squares earth rotation parameter prediction algorithm will cause the data saturation and the old and new data in the data processing and forecasting are equally treated and so on t,he forgetting factor into the least squares prediction algorithm ,and thus improve the accuracy of ERP forecast.The forgetting factor recursive least squares algorithm can prevent data saturation , reduce the influence of old data, strengthen the function of new data,reduce the probability of inversion matrix of rank loss matrix when solving the fitting parameters ,and improve the prediction accuracy.In this paper, the least squares expression of forgetting factor is deduced in detail , and the best forgetting factor is explored.The experimental results of this method and the results of LS -AR model are compared with those of LSA-R model .The least squares model prediction of the forgetting factor can achieve the same accuracy as the LS-AR model. |
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| Keywords: | earth rotation parameters forecasting forgetting factor the recursive least squares |
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