Prediction of Global Ionospheric Map Using the Theory of Maximum Posterior Estimation
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摘要: 提出了一种基于极大验后估计理论的全球电离层预报方法，基于中国科学院电离层分析中心（CAS）提供的快速全球电离层地图（GIM），实现了1天、2天和5天GIM的预报。以国际GNSS服务组织（IGS）最终GIM、Jason测高卫星提供的电离层观测信息及全球GNSS基准站实测电离层总电子含量（TEC）为基准，评估了2008－2017年CAS电离层预报GIM在全球大陆及海洋区域的精度，并与欧洲定轨中心（CODE）、欧洲空间局（ESA）和西班牙加泰罗尼亚理工大学（UPC）的预报GIM进行对比。在评估时段内，与IGS-GIM相比，CAS预报GIM精度为2.4~3.1 TECU；与测高卫星TEC相比，CAS预报GIM的精度为5.1~6.6 TECU；与全球基准站实测TEC相比，CAS预报GIM的电离层延迟修正精度优于80%。总体来看，CAS预报GIM与CODE预报GIM精度相当，显著优于ESA和UPC预报GIM。Abstract: A method based on maximum posterior estimation is proposed for the prediction of global ionosphere. Using the rapid ionospheric products from the Chinese Academy of Sciences (CAS), the 1-, 2- and 5-day predicted Global Ionospheric Maps (GIM) are routinely generated with the proposed algorithm. The qualities of CAS predicted GIMs as well as those from the Center for Orbit Determination of Europe (CODE), European Space Agency (ESA) and the Polytechnic University of Catalonia (UPC), are evaluated during 2008-2017 using Total Electron Content (TEC) references derived from the final GIMs of the International GNSS Service (IGS), Jason altimetry and global GNSS reference stations. The consistency between CAS predicted GIMs and IGS final GIMs is 2.4~3.1 TECU during the test period. Compared to Jason derived TEC observables, the precision of CAS predicted GIMs is on the level of 5.1~6.6 TECU over global oceanic regions. Compared to the TECs derived by global reference stations, the ionospheric delay correction accuracy of CAS predicted GIMs is better than 80%. Overall, the quality of CAS predicted GIM performs at the same level with that from CODE, which is significantly better than ESA and UPC predicted ones.
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图 1 电离层零阶球谐系数时间序列及其功率谱分析
Figure 1. Zero-order spherical harmonic coefficient time series and its spectrum analysis diagram
图 2 不同预报GIM与IGSG相比电离层VTEC残差频率分布的直方图（2015年6月29 日06:00:00 UTC）
Figure 2. Ionospheric TEC residual histogram of different predicted GIMs compared to IGSG at 06:00:00 UTC on 29 June 2015
图 3 2008－2017年CAS，CODE，ESA，UPC预报1天和2天GIM的RMS序列
Figure 3. RMS series of CAS/CODE/ESA/UPC 1- and 2-day predicted GIMs compared to IGS-GIM during 2008－2017
图 4 不同预报GIM随地理纬度和地方时的分布
Figure 4. Global VTEC map in geographic latitude and local time coordinates
图 5 不同预报GIM与Jason-2 VTEC相比残差随地理纬度和地方时的分布
Figure 5. Different predicted GIMs difference map in geographic latitude and Local Time (LT) coordinates compared to Jason-2 VTEC
图 6 不同预报GIM与Jason-2 TEC 相比的Bias（a）和 STD（b）随时间的变化
Figure 6. Different predicted GIMs bias (a) and STD (b) with time compared to Jason-2 TEC
图 7 预报的GIM-TEC与实测的测站上空TEC对比
Figure 7. Comparison between the predicted GIM-TEC and the measured TEC over the station
表 1 2008－2017年CAS，CODE，ESA，UPC预报1天和2天GIM与IGS-GIM相比的精度统计
Table 1. Analysis result of CAS, CODE, ESA, UPC 1- and 2-day predicted GIMs compared with IGS-GIM from 2008 to 2017
机构 测评时长/d 精度/TECU 相对误差/(%) 偏差 STD RMS CASP1 3640 –0.79 2.79 3.06 18.7 CODP1 3636 –0.68 2.78 3.02 18.4 ESAP1 1885 –0.98 3.86 4.13 21.4 CASP2 3640 –0.73 2.14 2.45 19.7 CODP2 3637 –0.58 1.98 2.32 18.5 ESAP2 1848 –0.96 3.02 3.33 22.1 UPCP2 1919 0.58 3.44 4.32 26.8 
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表 2 2008－2016年CAS，CODE，ESA 及UPC 预报GIM与Jason-2 TEC 相比的精度统计
Table 2. Analysis result of CAS, CODE, ESA and UPC predicted GIMs compared with Jason-2 TECs during 2008－2016
机构 测评时长/d 精度/TECU 相对误差/(%) 偏差 STD RMS CASP1 3074 0.41 4.79 5.09 25.3 CODP1 3070 0.31 4.88 5.17 25.8 ESAP1 1869 0.43 5.87 6.08 27.8 CASP2 3074 0.42 4.89 5.31 26.4 CODP2 3071 0.38 4.85 5.19 26.0 ESAP2 1836 0.46 6.12 6.49 29.6 UPCP2 1888 1.99 5.47 6.67 28.5 CASP5 3074 0.48 5.97 6.58 32.6
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表 3 CODE与CAS预报GIM与实测的dSTEC相比的精度统计
Table 3. Analysis result of CODE and CAS predicted GIMs compared with GPS-dSTEC
机构 精度/TECU 相对误差/(%) 偏差 STD RMS CASP1 0.06 2.32 2.40 16.9 CODP1 0.16 2.35 2.43 16.5 CASP2 0.07 2.35 2.44 17.4 CODP2 0.13 2.34 2.49 16.9 CASP5 0.07 2.81 2.91 20.6
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[1] CHEN Junping, LI Haojun, WU Bin, et al. Performance of real-time precise point positioning[J]. Marine Geodesy, 2013, 36(1): 98-108 doi: 10.1080/01490419.2012.699503 [2] 丁文武, 欧吉坤, 李子申, 等. 附加电离层延迟约束的实时动态PPP快速重新初始化方法[J]. 地球物理学报, 2014, 57(6): 1720-1731 doi: 10.6038/cjg20140604DING Wenwu, OU Jikun, LI Zishen, YUAN Yunbin. Instantaneous re-initialization method of real time kinematic PPP by adding ionospheric delay constraints[J]. Chinese Journal of Geophysics, 2014, 57(6): 1720-1731 doi: 10.6038/cjg20140604 [3] LI Zishen, WANG Ningbo, HERNÁNDEZ-PAJARES Manuel, et al. IGS real-time service for global ionospheric total electron content modeling[J]. Journal of Geodesy, 2020, 94(3): 1-16 [4] YANG Heng, MONTE-MORENO Enric, HERNÁNDEZ-PAJARES Manuel, et al. Real-time interpolation of global ionospheric maps by means of sparse representation[J]. Journal of Geodesy, 2021, 95(6): 1-20 [5] 王喜江, 边少锋, 李子申, 等. 利用半参数核估计法预报全球电离层总电子含量[J]. 地球物理学报, 2020, 63(4): 1271-1281WANG XiJiang, BIAN Shaofeng, LI Zishen, et al. 2020. Prediction of global ionospheric TEC using the semiparametric kernel estimation method[J]. Chinese Journal of Geophysics, 63(4): 1271-1281 [6] RATNAM D Venkata, OTSUKA Yuichi, SIVAVARAPRASAD G, et al. Development of multivariate ionospheric TEC forecasting algorithm using linear time series model and ARMA over low-latitude GNSS station[J]. Advances in Space Research, 2019, 63(9): 2848-2856 doi: 10.1016/j.asr.2018.03.024 [7] REN Xiaodong, WU Fengbo, ZHANG Xiaohong, et al. Short-term prediction of ionospheric TEC based on ARIMA model[J]. Acta Geodaetica et Cartographica Sinica, 2020, 2(1): 9-16 [8] 崔希璋. 广义测量平差[M]. 第2版. 武汉: 武汉大学出版社, 2009CUI Xizhang. Generalized Survey Adjustment[M]. second edition. Whuhan: Wuhan University Press, 2009 [9] 张强, 章红平, 赵齐乐, 等. 利用最小二乘配置预报全球电离层总电子含量[J]. 大地测量与地球动力学, 2014, 34(6): 86-91 doi: 10.14075/j.jgg.2014.06.017ZHANG Qiang, ZHANG Hongping, ZHAO Qile, et al. Global Ionospheric TEC Prediction Based on Least-Squares Collocation Method[J]. Journal of Geodesy and Geodynamics, 2014, 34(6): 86-91 doi: 10.14075/j.jgg.2014.06.017 [10] TEBABAL A, RADICELLA Sm, NIGUSSIE M, et al. Local TEC modelling and forecasting using neural networks[J]. Journal of Atmospheric and Solar-Terrestrial Physics, 2018, 172: 143-151 doi: 10.1016/j.jastp.2018.03.004 [11] XU Fulong, LI Zishen, ZHANG Kefei, et al. An Investigation of Optimal Machine Learning Methods for the Prediction of ROTI[J]. Journal of Geodesy and Geoinformation Science, 2020, 3(2): 1 [12] 张富彬, 周晨, 王成, 等. 基于深度学习的全球电离层TEC预测[J]. 电波科学学报, 2021, 36(4): 553-561 doi: 10.13443/j.cjors.2020051101ZHANG F B, ZHOU C, WANG C, et al. Global ionospheric TEC prediction based on deep learning[J]. Chinese Journal of Radio Science, 2021, 36(4): 553-561 doi: 10.13443/j.cjors.2020051101 [13] LI Min, YUAN Yunbin, WANG Ningbo, et al. Performance of various predicted GNSS global ionospheric maps relative to GPS and JASON TEC data[J]. GPS Solutions, 2018, 22(2): 55 doi: 10.1007/s10291-018-0721-2 [14] GARCÍA-RIGO A, MONTE E, Hernández-Pajares M, et al. Global prediction of the vertical total electron content of the ionosphere based on GPS data[J]. Radio science, 2011, 46(6): 1-3 [15] SCHAER S, Géodésique Société Helvétique Des Sciences Naturelles. Commission. Mapping and Predicting the Earth’s Ionosphere Using the Global Positioning System[M]. Institut für Geodäsie und Photogrammetrie, Eidg. Technische Hochschule Zürich, 1999 [16] 李子申, 王宁波, 李敏, 等. 国际 GNSS 服务组织全球电离层 TEC 格网精度评估与分析[J]. 地球物理学报, 2017, 60(10): 3718-3729 doi: 10.6038/cjg20171003LI Zishen, WANG Ningbo, LI Min, et al. Evaluation and analysis of the global ionospheric TEC map in the frame of international GNSS services[J]. Chinese Journal of Geophysics, 2017, 60(10): 3718-3729 doi: 10.6038/cjg20171003 [17] HERNÁNDEZ-PAJARES M, JUAN Jm, SANZ J, et al. The IGS VTEC maps: a reliable source of ionospheric information since 1998[J]. Journal of Geodesy, 2009, 83(3/4): 263-275 [18] 张强, 赵齐乐. 武汉大学 IGS 电离层分析中心全球电离层产品精度评估与分析[J]. 地球物理学报, 2019, 62(12): 4493-4505ZHANG Qiang, ZHAO Qile. 2019. Evaluation and analysis of the global ionosphere maps from Wuhan University IGS Ionosphere Associate Analysis Center[J]. Chinese Journal of Geophysics, 62(12): 4493-4505 [19] LI Zishen, WANG Ningbo, LIU Ang, et al. Status of CAS global ionospheric maps after the maximum of solar cycle 24[J]. Satellite Navigation, 2021, 2(1): 1-15 doi: 10.1186/s43020-020-00033-9 [20] 李子申. GNSS/compass电离层时延修正及TEC监测理论与方法研究[D]. 武汉: 中国科学院测量与地球物理研究所, 2012LI Zishen. Research on Theory and Method of GNSS/Compass Ionospheric Delay Correction and TEC Monitoring[D]. Wuhan: Institute of Surveying and Geophysics, Chinese Academy of Sciences, 2012 [21] 周江文. 拟合推估新解之一——两步解法[J]. 测绘学报, 2002, 31(3): 189-191 doi: 10.3321/j.issn:1001-1595.2002.03.001ZHOU Jiangwen. One of the new solutions for fitting estimation——two-step solution[J]. Acta Geodaetica et Cartographica Sinica, 2002, 31(3): 189-191 doi: 10.3321/j.issn:1001-1595.2002.03.001 [22] STOICA P, MOSES RANDOLPH L. Spectral Analysis of Signals[M]. Upper Saddle River: Prentice Hall, 2005 [23] REDDYBATTULA K Durga, PANDA S Kumar, ANSARI K, et al. Analysis of ionospheric TEC from GPS, GIM and global ionosphere models during moderate, strong, and extreme geomagnetic storms over Indian region[J]. Acta Astronautica, 2019, 161: 283-292 doi: 10.1016/j.actaastro.2019.05.042 [24] 王宁波, 袁运斌, 李子申, 等. 不同NeQuick电离层模型参数的应用精度分析[J]. 测绘学报, 2017, 46(4): 421-429 doi: 10.11947/j.AGCS.2017.20160400WANG Ningbo, YUAN Yunbin, LI Zishen, et al. Performance Analysis of Different NeQuick Ionospheric Model Parameters[J]. Acta Geodaetica et Cartographica Sinica, 2017, 46(4): 421-429 doi: 10.11947/j.AGCS.2017.20160400 [25] LIU Ang, WANG Ningbo, LI Zishen, et al. Assessment of NeQuick and IRI-2016 models during different geomagnetic activities in global scale: comparison with GPS-TEC, dSTEC, Jason-TEC and GIM[J]. Advances in Space Research, 2019, 63(12): 3978-3992 doi: 10.1016/j.asr.2019.02.032 [26] HERNÁNDEZ-PAJARES M, ROMA-DOLLASE D, KRANKOWSKI A, et al. Methodology and consistency of slant and vertical assessments for ionospheric electron content models[J]. Journal of Geodesy, 2017, 91(12): 1405-1414 doi: 10.1007/s00190-017-1032-z -
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