两种高程坐标预测模型的精度对比分析
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摘要
为提高IGS测站高程坐标预测精度,分别拟合两种时间序列模型:多项式周期模型与ARMA模型,选用我国及周边7个IGS站2013年的观测数据进行实验验证及对比分析。结果表明:两种模型的预报中误差均小于4.5 mm,可作为高程坐标预测的参考模型,同时,ARMA模型的预报精度较多项式周期模型的预报精度提升5%以上,且稳定性高于多项式周期模型,更加适合站点的坐标预报。
In order to improve the accuracy of elevation coordinate prediction in IGS station, two time series models are fitted, respectively: polynomial periodic model and ARMA model, and the experimental verification and comparative analysis of 7 IGS stations in China and its surrounding IGS stations in 2013 are carried out. The results show that the prediction error of the two models is less than 4.5 mm, which can be used as a reference model for the prediction of elevation coordinates, meanwhile, the prediction accuracy of the ARMA model is more than 5% higher than that of the polynomial periodic model, and the stability is higher than that of the polynomial periodic model, which is more suitable for the site coordinate prediction.
In order to improve the accuracy of elevation coordinate prediction in IGS station, two time series models are fitted, respectively: polynomial periodic model and ARMA model, and the experimental verification and comparative analysis of 7 IGS stations in China and its surrounding IGS stations in 2013 are carried out. The results show that the prediction error of the two models is less than 4.5 mm, which can be used as a reference model for the prediction of elevation coordinates, meanwhile, the prediction accuracy of the ARMA model is more than 5% higher than that of the polynomial periodic model, and the stability is higher than that of the polynomial periodic model, which is more suitable for the site coordinate prediction.
引文
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[16] 黄立人.GPS基准站坐标分量时间序列的噪声特性分析[J].大地测量与地球动力学,2006(2):31-33,38.
[17] CHEN Q,VAN DAM T,SNEEUW N,et al.Extracting seasonal signals from continuous GPS time series with modern statistical methods[J].Egu General Assembly,2012,72(12):4801.
[18] GUALANDI A,SERPELLONI E,BELARDINELLI M E.Blind source separation problem in GPS time series[J].Journal of Geodesy,2016,90(4):323-341.
[19] 吕成亮,张胜凯,沈飞,等.基于共性误差的CORS站坐标时间序列分析[J].大地测量与地球动力学,2016,36(1):16-20.
[2] COLLILIEUX X,DAM T V,RAY J,et al.Strategies to mitigate aliasing of loading signals while estimating GPS frame parameters[J].Journal of Geodesy,2012,86(1):1-14.
[3] 张洪文,宋传峰,赵忠海.GPS站坐标时间序列的南极地壳运动监测[J].测绘科学,2016,41(9):25-28,41.
[4] DAM T V,WAHR J,MILLY P C D,et al.Crustal displacements due to continental water loading[J].Geophysical Research Letters,2001,28(4):651-654.
[5] 张鹏,蒋志浩,秘金钟,等.我国GPS跟踪站数据处理与时间序列特征分析[J].武汉大学学报(信息科学版),2007(3):251-254.
[6] 武曙光.区域CORS站坐标时间序列特征分析[D].武汉:武汉大学,2017.
[7] 曲国庆,苏晓庆.GPS时间序列小波相干分析[J].煤炭学报,2010,35(3):463-466.
[8] 马俊,姜卫平,周晓慧,等.联合小波和方差分量估计方法分析中国IGS测站时间序列变化特征[J].武汉大学学报(信息科学版),2017(7):1-8.
[9] 周亚,王立峰,张思慧,等.IGS连续运行参考站高程时间序列功率谱分析[J].太赫兹科学与电子信息学报,2014,12(1):103-107.
[10] 唐毅,刘卫宁,孙棣华,等.改进时间序列模型在高速公路短时交通流量预测中的应用[J].计算机应用研究,2015,32(1):146-149.
[11] BOUILLE F,CAZENAVE A,CRETAUX J F,et al.Geocenter Variations Derived from 5 Years of Data of the Doris Space System.Comparison with Surface Loading Data[J].1999.
[12] 王鑫,吴际,刘超,等.奇异谱分析在故障时间序列分析中的应用[J].北京航空航天大学学报,2016,42(11):2321-2331.
[13] 张九宴,张健.青岛市连续运行基准站系统(QDCORS)稳定性分析[J].大地测量与地球动力学,2017,37(9):923-927.
[14] GAZEAUX J,WILLIAMS S,KING M,et al.Detecting offsets in GPS time series:First results from the detection of offsets in GPS experiment[J].Journal of Geophysical Research Solid Earth,2013,118(5):2397-2407.
[15] 李蕾,葛悉佑,王静涛.极大似然法南极大陆IGS站时间序列分析[J].测绘科学,2016(7):1-13.
[16] 黄立人.GPS基准站坐标分量时间序列的噪声特性分析[J].大地测量与地球动力学,2006(2):31-33,38.
[17] CHEN Q,VAN DAM T,SNEEUW N,et al.Extracting seasonal signals from continuous GPS time series with modern statistical methods[J].Egu General Assembly,2012,72(12):4801.
[18] GUALANDI A,SERPELLONI E,BELARDINELLI M E.Blind source separation problem in GPS time series[J].Journal of Geodesy,2016,90(4):323-341.
[19] 吕成亮,张胜凯,沈飞,等.基于共性误差的CORS站坐标时间序列分析[J].大地测量与地球动力学,2016,36(1):16-20.