CORS coordinate time series preprocessing and software implementation in Sichuan-Tibet area
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摘要: 本文针对川藏地区连续运行参考站系统(continuously operating reference stations, CORS)基准站站点坐标包含复杂影响因子和丰富且微弱有益的信号的特点，为了解决区域大规模时间序列数据分析处理过程繁琐，且无法大批量处理的问题，设计开发了GNSS坐标时间序列预处理系统，支持大区域多站点批处理解算模式，实现数据产品预处理、下载和可视化，实现了最小二乘拟合、粗差剔除、建模插值和共模误差(common mode error，CME)改正等一体化功能模块的集成. 采用陆态网长期坐标时间序列数据从解算精度与效率两方面对软件进行了性能评估. 结果表明：陆态网各测站N方向和E方向最小二乘拟合的拟合优度R2均约在99%，拟合效果较好；粗差剔除后的时间序列相比于剔除前各方向的WRMS值都有降低；水平方向插值后的结果均方根误差(root mean square error, RMSE)值均优于8 mm. CME剔除后，水平方向和垂直方向均方根(root mean square, RMS)值均有所下降.
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关键词:
- GNSS /
- 时间序列 /
- 建模与插值 /
- 共模误差(CME)改正 /
- 批处理
Abstract: In this paper ,aiming at the characteristics of the site coordinates of the continuously operating reference stations (CORS) in Sichuan-Tibet region containing complex influence factors and abundant and weak beneficial signals ,in order to solve the problem that the regional large-scale time series data analysis and processing process is cumbersome and cannot be processed in large quantities, this paper designs and develops a GNSS coordinate time series preprocessing system, which supports the multi-site batch solving mode of large area, realizes data product preprocessing, download and visualization, and realizes least squares fitting, coarse rejection, and integration of integrated functional modules such as modeling interpolation and common-mode error correction. The long-term coordinate time series data of the crustal movement observation network of China (CMONOC) is used to evaluate the performance of the software from the aspects of solution accuracy and efficiency. The results show that the goodness of fit R2 of the least squares fitting in the N direction and E direction of each station in the CMONOC is about 99%, and the fitting effect is good. The WRMS values of the time series after coarse rejection are lower than those in all directions before rejection. The RMSE values of the results after horizontal interpolation are better than 8 mm. After the common-mode error is removed, the RMS values in both the horizontal and vertical directions decrease. -
表 1 西南区域部分IGS站坐标时间序列概况
测站 概率纬度/(°) 概略经度/(°) 时间跨度 实际观测历元数 历元总数 LHAS 29.66 91.10 1999.16301—2021.23425 7254 8063 LUZH 28.87 105.41 1999.16301—2021.23151 7943 8062 SCBZ 31.84 106.74 2010.49726—2021.23425 3740 3923 SCDF 30.98 101.12 2010.00411—2019.04247 2880 2937 XZGZ 32.29 84.07 2012.18443—2021.18219 2760 3288 XZRK 29.25 88.87 2011.43699—2021.23425 3163 3580 SCJU 28.18 104.52 2010.49726—2021.23425 3760 3923 
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表 4 SCDF站时间序列各缺失段建模插值精度统计
缺失区间 起始历元 结束历元 缺失长度 RMSE/mm N E U 1 2011.08082 2011.16027 30 0.93 1.47 2.96 2 2012.70902 2012.87022 60 2.25 1.83 10.82 3 2013.90548 2014.14932 90 2.16 3.58 11.10 4 2016.40847 2016.73361 120 1.99 4.77 7.72 5 2017.27260 2017.68356 150 2.50 4.25 6.88 6 2018.16301 2018.65342 180 2.84 2.43 6.56
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[1] 徐华卿. GNSS坐标时间序列粗差探测与噪声估计研究 [D]. 南昌: 东华理工大学, 2022. [2] 姜卫平, 李昭, 刘万科, 等. 顾及非线性变化的地球参考框架建立与维持的思考[J]. 武汉大学学报(信息科学版), 2010, 35(6): 665. [3] 苏利娜, 张勇. GPS 时间序列中同震和震后形变的自动识别和估计[J]. 武汉大学学报(信息科学版), 2018, 43(10): 1504-1510. [4] BLEWITT G, KREEMER C, HAMMOND W C, et al. Rapid determination of earthquake magnitude using GPS for tsunami warning systems[J]. Geophysical research letters, 2006, 33(11): 11309. DOI: 10.1029/2006GL026145 [5] WÖPPELMANN G, MIGUEZ B M, BOUIN M-N, et al. Geocentric sea-level trend estimates from GPS analyses at relevant tide gauges world-wide[J]. Global and planetary change, 2007, 57(3-4): 396-406. DOI: 10.1016/J.GLOPLACHA.2007.02.002 [6] KING M A, ALTAMIMI Z, BOEHM J, et al. Improved constraints on models of glacial isostatic adjustment: a review of the contribution of ground-based geodetic observations[J]. Surveys in geophysics, 2010(31): 465-507. DOI: 10.1007/S10712-010-9100-4 [7] 蔡富. GNSS测站坐标非线性变化的全球分布规律与部分机制研究 [D]. 郑州: 战略支援部队信息工程大学, 2020. [8] 张恒璟, 程鹏飞. 基于 GPS 高程时间序列粗差的抗差探测与插补研究[J]. 大地测量与地球动力学, 2011, 31(4): 71-75. [9] HERRING T. MATLAB Tools for viewing GPS velocities and time series[J]. GPS solutions, 2003, 7(3): 194-199. DOI: 10.1007/S10291-003-0068-0 [10] WILLIAMS S D. CATS: GPS coordinate time series analysis software[J]. GPS solutions, 2008, 12(2): 147-153. DOI: 10.1007/S10291-007-0086-4 [11] 舒颖, 花向红, 贺小星, 等. GPS 时间序列数据处理与分析软件的设计及实现[J]. 2017, 42(5): 29-32. [12] NIKOLAIDIS R. Observation of geodetic and seismic deformation with the Global Positioning System [M]. University of California, San Diego, 2002. [13] 舒颖. GPS坐标时间序列粗差剔除方法比较分析[J]. 导航定位学报, 2021, 9(4): 79-85. [14] 杨登科. 不同插值方法对GPS时间序列的影响分析[J]. 全球定位系统, 2019, 44(5): 66-69. [15] LANGBEIN J. Noise in GPS displacement measurements from Southern California and Southern Nevada[J]. Journal of geophysical research solid earth, 2008, 113(B5): B05405. DOI: 10.1029/2007JB005247 [16] BLEWITT G, LAVALLÉE D. Effect of annual signals on geodetic velocity[J]. Journal of geophysical research:solid earth, 2002, 107(B7): 2145. DOI: 10.1029/2001JB000570 [17] DAVIS J L, WERNICKE B P, TAMISIEA M E. On seasonal signals in geodetic time series[J]. Journal of geophysical research, 2012, 117(B1): B01403. DOI: 10.1029/2011JB008690 [18] 冯胜涛, 刘雪龙, 王友. 最小二乘拟合GNSS位置时间序列分析[J]. 测绘科学, 2015, 40(10): 157-160. [19] DONG D, FANG P, BOCK Y, et al. Spatiotemporal filtering using principal component analysis and Karhunen‐Loeve expansion approaches for regional GPS network analysis[J]. Journal of geophysical research:solid earth, 2006, 111(B3): B03405. DOI: 10.1029/2005JB003806 [20] 伍吉仓, 孙亚峰, 刘朝功. 连续 GPS 站坐标序列共性误差的提取与形变分析[J]. 大地测量与地球动力学, 2008, 28(4): 97-101. -
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