Two Improved Algorithms for LS+AR Prediction Model of the Polar Motion

doi:10.11947/j.AGCS.2018.20180296

Abstract

Abstract: The polar motion(PM) is the important parameter to represent the earth movement, and the high-precision prediction of PM plays a key role in practical applications of astronomical research, the geodetic survey, navigation, aviation, ocean sounding and interplanetary navigation. Two modified algorithms are proposed to improve the PM prediction accuracy based on combination of least square and autoregressive model (LS+AR). One is to combine Kalman filtering (KF) to improve AR model accuracy, namely LS+AR+KF algorithm. The other is to use least mean square adaptive filtering (LMSAF) to improve the accuracies of LS fitting terms and predicting extrapolations, namely LS+AR+AF algorithm. The results show that LS+AR+KF and LS+AR+AF algorithms can significantly enhance the prediction accuracy of PM especially for long-term perdition, and LS+AR+AF is obviously superior to LS+AR and LS+AR+KF for PM prediction. The accuracy improvement of PM X component, PM Y component and PM can reach about 26%, 23% and 24% respectively, when using LS+AR+AF algorithm.

Key words: polar motion, prediction, Kalman filtering, least mean square, adaptive filtering

CLC Number:

P228

JIA Song, XU Tianhe, YANG Honglei. Two Improved Algorithms for LS+AR Prediction Model of the Polar Motion[J]. Acta Geodaetica et Cartographica Sinica, 2018, 47(S0): 71-77.

References

[1] 郑大伟, 陈兆国. 地球自转参数预测[J]. 中国科学院上海天文台年刊, 1982(4):116-120. ZHENG Dawei, CHEN Zhaoguo. Predictions of the Earth Rotation Parameters[J]. Annals of Shanghai Observatory Academia Sinica, 1982(4):116-120.
[2] 周永宏, 郑大伟, 廖新浩. 日长变化, 大气角动量和ENSO:1997-1998厄尔尼诺和1998-1999拉尼娜信号[J]. 测绘学报, 2001, 30(4):288-292. DOI:10.3321/j.issn:1001-1595.2001.04.003. ZHOU Yonghong, ZHENG Dawei, LIAO Xinhao. Length-of-day Variation, Atmosphere Angular Momentum and ENSO:Signatures of 1997-1998 and 199-1999 ENSO Events[J]. Acta Geodaetica et Cartographica Sinica, 2001, 30(4):288-292. DOI:10.3321/j.issn:1001-1595.2001.04.003.
[3] WANG Qianxin, HU Chao, XU Tianhe, et al. Impacts of Earth Rotation Parameters on GNSS Ultra-rapid Orbit Prediction:Derivation and Real-time Correction[J]. Advances in Space Research, 2017, 60(12):2855-2870.
[4] 张卫星, 李征航, 刘万科. EOP预报误差对导航卫星自主定轨影响分析[C]//第二届中国卫星导航学术年会电子文集. 上海:中国卫星导航学术年会组委会, 2011. ZHANG Weixing, LI Zhenghang, LIU Wanke. Influence of EOP Prediction Error on Autonomous Orbit Determination of Navigation Satellite[C]//China Satellite Navigation Conference (CSNC) 2011 Proceedings. Shanghai:China Satellite Navigation Conference, 2011.
[5] 张捍卫, 许厚泽, 周旭华. 液核地球极移和章动理论模型的改进[J]. 测绘学报, 2006, 35(3):215-219. ZHANG Hanwei, XU Houze, ZHOU Xuhua. A Theoretical Improvement on Wobble and Nutation of Flui Core Earth Model[J]. Acta Geodaetica et Cartographica Sinica, 2006, 35(3):215-219.
[6] 雷雨. 地球自转参数高精度预报方法研究[D]. 西安:中国科学院大学(国家授时中心), 2016. LEI Yu. Study on Methods for High Accuracy Prediction of Earth Rotation Parameters[D]. Xi'an:University of Chinese Academy of Sciences, 2016.
[7] 柳文明, 李峥嵘, 刘文祥, 等. EOP预报误差对导航卫星轨道预报的影响分析[J]. 全球定位系统, 2009, 34(6):17-22, 27. LIU Wenming, LI Zhengrong, LIU Wenxiang, et al. Influence of EOP Prediction Errors on Orbit Prediction of Navigation Satellites[J]. GNSS World of China, 2009, 34(6):17-22, 27.
[8] SUN Zhangzhen, XU Tianhe. Prediction of Earth Rotation Parameters Based on an Improved Weighted Least Squares and Autoregressive Model[J]. Geodesy and Geodynamics, 2012, 3(3):57-64.
[9] 姚宜斌, 岳顺强, 陈鹏. 一种适用于极移预报的附加误差修正的LS+AR新模型[J]. 中国科学(地球科学), 2013, 43(4):665-676. YAO Yibin, YUE Shunqiang, CHEN Peng. A New LS+AR Model with Additional Error Correction for Polar Motion Forecast[J]. Science China Earth Sciences, 2013, 56(5):818-828, DOI:10.1007/s11430-012-4572-3.
[10] 许雪晴, 周永宏. 地球定向参数高精度预报方法研究[J]. 飞行器测控学报, 2010, 29(2):70-76. XU Xueqing, ZHOU Yonghong. High Precision Prediction Method of Earth Orientation Parameters[J]. Journal of Spacecraft TT &C Technology, 2010, 29(2):70-76.
[11] 王琪洁. 基于神经网络技术的地球自转变化预报[D]. 上海:中国科学院研究生院(上海天文台), 2007. WANG Qijie. Studies on the Prediction of Earth's Variable Rotation by Artificial Neural Networks[D]. Shanghai:Shanghai Astronomical Observatory, Chinese Academy of Sciences, 2007.
[12] SHEN Yi, GUO Jinyun, LIU Xin, et al. Long-term Prediction of Polar Motion Using a Combined SSA and ARMA Model[J]. Journal of Geodesy, 2018, 92(3):333-343.
[13] DOBSLAW H, DILL R. Predicting Earth Orientation Changes from Global Forecasts of Atmosphere-Hydrosphere Dynamics[J]. Advances in Space Research, 2017, 61(4):1047-1054.
[14] KOSEK W, KALARUS M, NIEDZIELSKI T. Forecasting of the Earth Orientation Parameters-comparison of Different Algorithms[M]//CAPITAINE N. Proceedings of the Journées Systèmes de Référence Spatio-temporels 2007. Observatoire de Paris:[s.n.], 2007.
[15] 韩永志, 马利华, 尹志强. 极移振幅主要周期分量的时变特征[J]. 地球物理学进展, 2006, 21(3):798-801. HAN Yongzhi, MA Lihua, YIN Zhiqiang. Time-variation of Periodic Components of Polar Motion Amplitude[J]. Progress in Geophysics, 2006, 21(3):798-801.
[16] CHAO B F, GROSS R S. Changes in the Earth's Rotational Energy Induced by Earthquakes[J]. Geophysical Journal of the Royal Astronomical Society, 2010, 122(3):776-783.
[17] HUANG Mei, ZHU Lin, GONG He, et al. Close Correlation Between Global Air Temperature Change and Polar Motion During 1962-2013[J]. Journal of Geophysical Research:Atmospheres, 2016, 121(19):11248-11263.
[18] JIN Shuanggen, HASSAN Ayman, FENG Guiping. Assessment of Terrestrial Water Contributions to Polar Motion from GRACE and Hydrological Models[J]. Journal of Geodynamics, 2012, 62(1):40-48. DOI:10.1016/j.jog.2012.01.009.
[19] JIN Shuanggen, CHAMBERS D P, TAPLEY B D. Hydrological and Oceanic Effects on Polar Motion from GRACE and Models[J]. Journal of Geophysical Research:Solid Earth, 2010, 115(B2):B02403. DOI:10.1029/2009JB006635.
[20] WINSKA M, NASTULA J, SALSTEIN D. Hydrological Excitation of Polar Motion by Different Variables from the GLDAS Models[J]. Journal of Geodesy, 2017, 91(12):1461-1473.
[21] 李毅. 自适应滤波及滤波算法研究[D]. 西安:西北工业大学, 2003. LI Yi. The Adaptive Filter and the Filtering Algorithm Research[D]. Xi'an:Northwestern Polytechnical University, 2003.
[22] 张勤, 张菊清, 岳东杰. 近代测量数据处理与应用[M]. 北京:测绘出版社, 2011. ZHANG Qin, ZHANG Juqing, YUE Dongjie. Advanced Theory and Application of Surveying Data[M]. Beijing:The Mapping Publishing, 2011.
[23] XU Xueqing, ZHOU Yonghong, LIAO Xinhao. Short-term Earth Orientation Parameters Predictions by Combination of the Least-squares, AR Model and Kalman Filter[J]. Journal of Geodynamics, 2012, 62:83-86.
[24] 徐天河, 杨元喜. 改进的Sage自适应滤波方法[J]. 测绘科学, 2000, 25(3):22-24. XU Tianhe, YANG Yuanxi. The Improved Method of Sage Adaptive Filtering[J]. Science of Surveying and Mapping, 2000, 25(3):22-24.
[25] YANG Yuanxi, HE Haibo, XU Guochang. Adaptively Robust Filtering for Kinematic Geodetic Positioning[J]. Journal of Geodesy, 2001, 75(2-3):109-116.
[26] 杨元喜, 景一帆, 曾安敏. 自适应参数估计与内外部精度的关系[J]. 测绘学报, 2014, 43(5):441-445. DOI:10.13485/j.cnki.11-2089.2014.0077. YANG Yuanxi, JING Yifan, ZENG Anmin. Adaptive Parameter Estimation and Inner and External Precision[J]. Acta Geodaetica et Cartographica Sinica, 2014, 43(5):441-445. DOI:10.13485/j.cnki.11-2089.2014.0077.