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Article(id=1322506322101252275, tenantId=1146029695717560320, journalId=1281212831689347082, issueId=1322506263716541212, articleNumber=null, orderNo=null, doi=10.14075/j.jgg.2024.09.436, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=research-article, receivedDate=1726675200000, receivedDateStr=2024-09-19, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1793239678168, onlineDateStr=2026-10-29, pubDate=1757865600000, pubDateStr=2025-09-15, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1793239678168, onlineIssueDateStr=2026-10-29, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1793239678168, creator=13701087609, updateTime=1793239678168, updator=13701087609, issue=Issue{id=1322506263716541212, tenantId=1146029695717560320, journalId=1281212831689347082, year='2025', volume='45', issue='9', pageStart='881', pageEnd='990', issueExtLink='null', onlineDate='null', pubDate='1757865600000', pubDateStr='2025-09-15', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1793239664248, creator='13701087609', updateTime=1793239664248, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext=null, issueFiles=null, downloadFileDto=null}, startPage=894, endPage=898, 904, ext={EN=ArticleExt(id=1322506322281607348, articleId=1322506322101252275, tenantId=1146029695717560320, journalId=1281212831689347082, language=EN, title=Accuracy Assessment of Earth Rotation Parameters Derived from VGOS and Synchronous S/X VLBI Solutions, columnId=null, journalTitle=Journal of Geodesy and Geodynamics, columnName=null, runingTitle=null, highlight=null, articleAbstract=

To assess the accuracy of Earth rotation parameters(ERP) derived from the current VLBI global observing system(VGOS) observational data, this paper processes data from VGOS observations made between 2019 and 2023. Simultaneously, traditional S-band and X-band VLBI observational data, which were obtained during the same periods as the VGOS data, were also included in the processing. The EOP 14 C04 series provided by the IERS were used as reference values for accuracy assessment. The results show that, during the selected experimental data periods, the average weighted root mean square(WRMS) of the post-fit residuals of time delay from VGOS observational data is 16.77 ps, which is significantly better than the 30.97 ps from the traditional S/X VLBI measurements during the same periods. In terms of ERP determination, there are still differences between the results from global network station observational data of VGOS and traditional S/X VLBI. Specifically, the ERP polar motion component accuracy derived from VGOS is inferior to that of traditional S/X VLBI, while the UT1-UTC accuracy is comparable to that of traditional S/X VLBI measurements. Further analysis using experimental stations centered on co-located stations indicates that VGOS measurements can provide ERP determination results with higher accuracy.

, authors=Huibin MA1, Wenzhen QIN1, Dan JIANG1, Changliang GENG1, Xin PENG1, authorsList=Huibin MA, Wenzhen QIN, Dan JIANG, Changliang GENG, Xin PENG, authorCompany=null, correspAuthors=null, authorNote=

MA Huibin, engineer, majors in space geodesy, E-mail:

, correspAuthorsNote=null, copyrightStatement=All rights reserved. Unauthorized reproduction is prohibited., copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1322506323766390975, articleId=1322506322101252275, tenantId=1146029695717560320, journalId=1281212831689347082, language=CN, title=基于VGOS与同步S/X VLBI解算地球自转参数的精度评估, columnId=1322506169105633839, journalTitle=大地测量与地球动力学, columnName=现代大地测量, runingTitle=null, highlight=null, articleAbstract=

为评估当前VLBI全球观测系统(VGOS)观测数据解算地球自转参数(ERP)的精度，基于2019—2023年VGOS观测数据进行解算，同时选取与VGOS观测数据同时段传统S频段、X频段的VLBI观测数据参与解算，以IERS提供的EOP 14 C04序列作为参考值进行精度评定。结果表明，在选取的实验数据时段，VGOS观测数据的时延拟合后残差加权均方根(WRMS)的平均值为16.77 ps，显著优于同时段传统S/X VLBI测量数据的30.97 ps。在ERP解算方面，VGOS和传统S/X VLBI的全球网络站观测数据的解算结果存在差异，其中，VGOS解算ERP极移分量的精度不如传统S/X VLBI，UT1-UTC精度与传统S/X VLBI测量相当。进一步选取以并址站为核心的实验站进行分析表明，VGOS测量能够提供更高精度的ERP解算结果。

, authors=马慧斌1, 秦文振1, 江丹1, 耿昌亮1, 彭鑫1, authorsList=马慧斌, 秦文振, 江丹, 耿昌亮, 彭鑫, authorCompany=null, correspAuthors=null, authorNote=

马慧斌，工程师，主要研究方向为空间大地测量学，E-mail：

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MA Huibin, engineer, majors in space geodesy, E-mail:

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马慧斌，工程师，主要研究方向为空间大地测量学，E-mail：

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马慧斌，工程师，主要研究方向为空间大地测量学，E-mail：

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Advances in Geosciences, 2019, 50, 49- 56, articleTitle=Combination of VLBI Intensive Sessions with GNSS for Generating Low Latency Earth Rotation Parameters, refAbstract=null), Reference(id=1322506335506247942, tenantId=1146029695717560320, journalId=1281212831689347082, articleId=1322506322101252275, doi=null, pmid=null, pmcid=null, year=null, volume=null, issue=null, pageStart=null, pageEnd=null, url=null, language=null, rfNumber=10, rfOrder=11, authorNames=null, journalName=null, refType=null, unstructuredReference=Nilsson T, Haas R, Varenius E. The Current and Future Performance of VGOS[C]. IVS 2022 General Meeting, Helsinki, 2022, articleTitle=null, refAbstract=null), Reference(id=1322506335590134023, tenantId=1146029695717560320, journalId=1281212831689347082, articleId=1322506322101252275, doi=null, pmid=null, pmcid=null, year=null, volume=null, issue=null, pageStart=null, pageEnd=null, url=null, language=null, rfNumber=11, rfOrder=12, authorNames=null, journalName=null, refType=null, unstructuredReference=Artz T, Böckmann S, Jensen L, et al. Reliability and Stability of VLBI-Derived Sub-Daily EOP Models[C]. 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Detailed information of the experimental stations

, figureFileSmall=null, figureFileBig=null, tableContent=
站名 观测代码 所属国家 ITU-所属区 经度 纬度
ONSA13SW Ow 瑞典 R1 57°23′38.8″ 11°55′8.4″
ONSA13NE Oe 瑞典 R1 57°23′38.4″ 11°55′12.0″
Ny-Alesund Nn 挪威 R1 78°56′34.8″ 11°51′18.0″
WETTZ13S Ws 德国 R1 49°8′34.8″ 12°52′40.8″
RAEGYEB Yj 西班牙 R1 40°31′22.8″ -3°5′16.8″
KOKEE12M K2 美国 R2 22°7′33.6″ -159°39′26.4″
ISHIOKA Is 日本 R3 36°6′10.8″ 140°5′20.4″
Hobart12 Hb 澳大利亚 R3 -42°48′21.6″ 147°26′16.8″
), ArticleFig(id=1322506332301799666, tenantId=1146029695717560320, journalId=1281212831689347082, articleId=1322506322101252275, language=CN, label=表1, caption=

实验台站详细信息

, figureFileSmall=null, figureFileBig=null, tableContent=
站名 观测代码 所属国家 ITU-所属区 经度 纬度
ONSA13SW Ow 瑞典 R1 57°23′38.8″ 11°55′8.4″
ONSA13NE Oe 瑞典 R1 57°23′38.4″ 11°55′12.0″
Ny-Alesund Nn 挪威 R1 78°56′34.8″ 11°51′18.0″
WETTZ13S Ws 德国 R1 49°8′34.8″ 12°52′40.8″
RAEGYEB Yj 西班牙 R1 40°31′22.8″ -3°5′16.8″
KOKEE12M K2 美国 R2 22°7′33.6″ -159°39′26.4″
ISHIOKA Is 日本 R3 36°6′10.8″ 140°5′20.4″
Hobart12 Hb 澳大利亚 R3 -42°48′21.6″ 147°26′16.8″
), ArticleFig(id=1322506332377297139, tenantId=1146029695717560320, journalId=1281212831689347082, articleId=1322506322101252275, language=EN, label=Tab. 2, caption=

Accuracy statistics of the solved results from different observations

, figureFileSmall=null, figureFileBig=null, tableContent=
ERP序列平均误差 加权均方根
VGOS S/X VLBI VGOS S/X VLBI
XP/mas 0.086 2 0.058 8 0.643 5 0.326 2
YP/mas 0.175 3 0.144 6 0.568 7 0.385 0
UT1-UTC/ms -0.009 8 -0.057 2 0.032 5 0.032 2
), ArticleFig(id=1322506332444406004, tenantId=1146029695717560320, journalId=1281212831689347082, articleId=1322506322101252275, language=CN, label=表2, caption=

不同观测解算结果的精度统计

, figureFileSmall=null, figureFileBig=null, tableContent=
ERP序列平均误差 加权均方根
VGOS S/X VLBI VGOS S/X VLBI
XP/mas 0.086 2 0.058 8 0.643 5 0.326 2
YP/mas 0.175 3 0.144 6 0.568 7 0.385 0
UT1-UTC/ms -0.009 8 -0.057 2 0.032 5 0.032 2
), ArticleFig(id=1322506332528292085, tenantId=1146029695717560320, journalId=1281212831689347082, articleId=1322506322101252275, language=EN, label=Tab. 3, caption=

VGOS observation information and the comprison of solution results involving the Hb segment with IERS data

, figureFileSmall=null, figureFileBig=null, tableContent=
观测时间 观测代码 台站数量 测站代码 XP/mas YP/mas UT1-UTC/ms
59 970.249 68 vr2301 11 GsHbK2KeMgNnOeOwSaWfYj 0.232 0.020 -0.023 7
60 069.249 68 vo3124 10 GsHbIsK2NnOeOwWfWsYj -0.046 -0.132 -0.009 3
60 096.249 68 vr2302 11 HbIsK2KeNnOeOwSaWfWsYj 0.105 0.052 -0.019 5
60 125.249 68 vo3180 10 GsHbK2MgNnOeOwWfWsYj -0.145 -0.285 -0.013 6
60 230.249 68 vo3285 10 GsHbIsK2MgOeOwSaWfYj 0.042 -0.190 0.012 1
60 265.249 68 vr2304 10 GsHbIsK2MgOeSaWfWsYj 0.040 -0.160 0.020 3
60 286.249 68 vo3341 10 GsHbIsK2MgOeSaWfWsYj -0.084 -0.176 0
60 292.249 68 vo3347 10 GsHbIsK2MgOeSaWfWsYj -0.035 -0.148 0.017 9
), ArticleFig(id=1322506332628955382, tenantId=1146029695717560320, journalId=1281212831689347082, articleId=1322506322101252275, language=CN, label=表3, caption=

Hb测段参与的VGOS观测信息及解算结果与IERS数据的比较

, figureFileSmall=null, figureFileBig=null, tableContent=
观测时间 观测代码 台站数量 测站代码 XP/mas YP/mas UT1-UTC/ms
59 970.249 68 vr2301 11 GsHbK2KeMgNnOeOwSaWfYj 0.232 0.020 -0.023 7
60 069.249 68 vo3124 10 GsHbIsK2NnOeOwWfWsYj -0.046 -0.132 -0.009 3
60 096.249 68 vr2302 11 HbIsK2KeNnOeOwSaWfWsYj 0.105 0.052 -0.019 5
60 125.249 68 vo3180 10 GsHbK2MgNnOeOwWfWsYj -0.145 -0.285 -0.013 6
60 230.249 68 vo3285 10 GsHbIsK2MgOeOwSaWfYj 0.042 -0.190 0.012 1
60 265.249 68 vr2304 10 GsHbIsK2MgOeSaWfWsYj 0.040 -0.160 0.020 3
60 286.249 68 vo3341 10 GsHbIsK2MgOeSaWfWsYj -0.084 -0.176 0
60 292.249 68 vo3347 10 GsHbIsK2MgOeSaWfWsYj -0.035 -0.148 0.017 9
), ArticleFig(id=1322506332738007288, tenantId=1146029695717560320, journalId=1281212831689347082, articleId=1322506322101252275, language=EN, label=Tab. 4, caption=

Accuracy statistics of different solutions

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REP序列平均误差 加权均方根
VGOS (Hb) S/X VLBI VGOS (Hb) S/X VLBI
XP/mas 0.013 60 0.058 8 0.111 60 0.326 2
YP/mas -0.127 40 0.144 6 0.164 40 0.385 0
UT1-UTC/ms -0.001 97 -0.057 2 0.016 17 0.032 2
), ArticleFig(id=1322506332830281977, tenantId=1146029695717560320, journalId=1281212831689347082, articleId=1322506322101252275, language=CN, label=表4, caption=

不同解算结果的精度统计

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REP序列平均误差 加权均方根
VGOS (Hb) S/X VLBI VGOS (Hb) S/X VLBI
XP/mas 0.013 60 0.058 8 0.111 60 0.326 2
YP/mas -0.127 40 0.144 6 0.164 40 0.385 0
UT1-UTC/ms -0.001 97 -0.057 2 0.016 17 0.032 2
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基于VGOS与同步S/X VLBI解算地球自转参数的精度评估
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马慧斌 1 , 秦文振 1 , 江丹 1 , 耿昌亮 1 , 彭鑫 1
大地测量与地球动力学 | 现代大地测量 2025,45(9): 894-898, 904
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大地测量与地球动力学 |现代大地测量 2025 , 45 (9) : 894 -898, 904
基于VGOS与同步S/X VLBI解算地球自转参数的精度评估
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马慧斌1 , 秦文振1, 江丹1, 耿昌亮1, 彭鑫1
作者信息
  • 1 61363部队，西安市，710054
作者简介:

马慧斌，工程师，主要研究方向为空间大地测量学，E-mail：

Accuracy Assessment of Earth Rotation Parameters Derived from VGOS and Synchronous S/X VLBI Solutions
Huibin MA1 , Wenzhen QIN1, Dan JIANG1, Changliang GENG1, Xin PENG1
Affiliations
  • 1 61363 Troops, Xi'an 710054, China

    • MA Huibin, engineer, majors in space geodesy, E-mail:

出版时间: 2025-09-15 doi: 10.14075/j.jgg.2024.09.436
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为评估当前VLBI全球观测系统(VGOS)观测数据解算地球自转参数(ERP)的精度，基于2019—2023年VGOS观测数据进行解算，同时选取与VGOS观测数据同时段传统S频段、X频段的VLBI观测数据参与解算，以IERS提供的EOP 14 C04序列作为参考值进行精度评定。结果表明，在选取的实验数据时段，VGOS观测数据的时延拟合后残差加权均方根(WRMS)的平均值为16.77 ps，显著优于同时段传统S/X VLBI测量数据的30.97 ps。在ERP解算方面，VGOS和传统S/X VLBI的全球网络站观测数据的解算结果存在差异，其中，VGOS解算ERP极移分量的精度不如传统S/X VLBI，UT1-UTC精度与传统S/X VLBI测量相当。进一步选取以并址站为核心的实验站进行分析表明，VGOS测量能够提供更高精度的ERP解算结果。

甚长基线干涉测量  /  VLBI全球观测系统  /  地球自转参数  /  时延拟合后残差

To assess the accuracy of Earth rotation parameters(ERP) derived from the current VLBI global observing system(VGOS) observational data, this paper processes data from VGOS observations made between 2019 and 2023. Simultaneously, traditional S-band and X-band VLBI observational data, which were obtained during the same periods as the VGOS data, were also included in the processing. The EOP 14 C04 series provided by the IERS were used as reference values for accuracy assessment. The results show that, during the selected experimental data periods, the average weighted root mean square(WRMS) of the post-fit residuals of time delay from VGOS observational data is 16.77 ps, which is significantly better than the 30.97 ps from the traditional S/X VLBI measurements during the same periods. In terms of ERP determination, there are still differences between the results from global network station observational data of VGOS and traditional S/X VLBI. Specifically, the ERP polar motion component accuracy derived from VGOS is inferior to that of traditional S/X VLBI, while the UT1-UTC accuracy is comparable to that of traditional S/X VLBI measurements. Further analysis using experimental stations centered on co-located stations indicates that VGOS measurements can provide ERP determination results with higher accuracy.

VLBI  /  VGOS  /  ERP  /  post-fit residuals of time delay
马慧斌, 秦文振, 江丹, 耿昌亮, 彭鑫. 基于VGOS与同步S/X VLBI解算地球自转参数的精度评估. 大地测量与地球动力学, 2025 , 45 (9) : 894 -898, 904 . DOI: 10.14075/j.jgg.2024.09.436
Huibin MA, Wenzhen QIN, Dan JIANG, Changliang GENG, Xin PENG. Accuracy Assessment of Earth Rotation Parameters Derived from VGOS and Synchronous S/X VLBI Solutions[J]. Journal of Geodesy and Geodynamics, 2025 , 45 (9) : 894 -898, 904 . DOI: 10.14075/j.jgg.2024.09.436
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VLBI全球观测系统(VLBI global observing system，VGOS)是国际大地测量和天体测量VLBI服务组织(International VLBI Service for Geodesy and Astrometry，IVS)推动建设，并于2021年起常态化运行的新一代测地VLBI观测系统。VLBI因其独具的超高空间分辨率和定位精度，一直是天体物理、天体测量和空间大地测量等领域的核心技术。VGOS作为VLBI测量技术的进化与发展，推动了VLBI技术的进步与应用，随着VGOS建设的不断完善，VGOS数据产品将逐步成为构建国际天球参考架、地球参考架和监测地球定向参数的重要数据源，广泛应用于天文学与地球科学研究、卫星导航和深空探测等领域[1-2]。
本文通过处理解算2019—2023年VGOS与传统S/X VLBI同步观测数据，并以IERS 14 C04序列为基础序列，分析VGOS与传统S/X VLBI观测数据解算地球自转参数(earth rotation parameters，ERP)序列的误差情况，初步探讨VGOS观测数据与传统S/X VLBI观测数据用于解算地球定向参数方面的精度差异。
1 同步观测数据选取与分析
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1.1 实验数据的获取
在2014年首次进行VGOS实验观测和2017年VLBI联测(CONT17)等初步全球测量工作完成后，产出一系列关于VGOS观测的数据可用于研究分析。虽然当前VGOS尚未实现连续观测，但是过去几年进行了大量的不同类别的VGOS观测实验，比如由1~3个基线组成的1 h加强型观测VGOS-2、VGOS-B，以及由多个基线组成的24 h观测VGOS-O，为研究VGOS解算地球自转参数提供了可供分析评估的实验数据[3]。本次实验选取CDDIS数据中心发布的2019—2023年vgosDb格式VGOS观测数据，以及同时段观测的IVS-R1、IVS-R4 S/X VLBI数据进行分析处理。在传统S/X VLBI观测方面，IVS服务组织每周一(IVS-R1)和每周四(IVS-R4)会组织约10个VLBI台站参与观测，形成传统VLBI快速周测段(the legacy VLBI rapid turnaround sessions)，该测段是以S频段和X频段为主的24 h观测数据，实验优先选用观测精度较高的XA、XE频率通道数据。在VGOS观测方面，由IVS主导的“VO观测”计划，已经开始每隔一周发布24 h观测数据(2022年曾每周发布)，并将每隔一周观测的VGOS测段安排与传统VLBI快速周测段进行同周期观测，这为对比VGOS与传统VLBI测量解算地球自转参数的精度分析提供了数据基础[4-5]。
1.2 实验站点选取
在实验站点选取方面，将站点选取分为全球网络观测站和以并址站为核心的实验站。根据不同的实验站点分别进行数据处理分析。全球网络观测站选取与“VO观测”计划中全球VGOS网络站作为VGOS网实验站点，同步选择传统S/X VLBI网中与“VO观测”计划同时段观测的全球VLBI测站，分别形成VGOS和传统VLBI各自代表的全球观测网络，用以评估同时段VGOS和传统S/X VLBI全球网络站观测数据解算ERP的精度差异。全球网络观测站选取的实验站点分布如图 1所示。总体而言，目前VGOS站点主要集中在北半球22.1°N和57.4°N之间，而传统VLBI站点全球分布较好。
并址站为核心的实验站优先选取与传统VLBI并址的VGOS网络站点(图 1中红色原点与绿色方块重合的站点)，这使得VGOS测站与传统VLBI测站可以在相同或者相近的观测网下进行比较，截至2023年底并址站点详细信息见表 1。Hobart12测站射电望远镜于2022年底加入IVS“VO观测”计划，作为VGOS网络目前唯一在南半球运行的测站，Hobart12测站的加入不但可用于评估相同网型结构下VGOS与传统VLBI观测数据用于解算ERP的差异，也可用于说明优化网型结构对VGOS解算ERP的影响。
1.3 观测数据分析
选取2019—2023年期间约130个测段的VGOS和同步S/X VLBI全球观测数据进行互相关处理，数据几乎覆盖5 a内的所有月份，分析结果如图 2所示。图的左侧Y轴显示观测数据统计结果，红点为VGOS观测数据量，蓝点为同时段S/X VLBI观测数据量；右侧Y轴表示各自观测数据的时延拟合后残差的加权均方根(weighted root mean square, WRMS)，图中红色折线表示VGOS数据，蓝色折线表示S/X VLBI数据。尽管VGOS测段每次参与的台站数(约7~9个)少于传统观测(约10~12个)，但是相比传统VLBI(S/X)站网只能选择S频段(约2 GHz)和X频段(约8 GHz)，VGOS可同时观测2~14 GHz频率范围内的4个频段，且比传统天线体积更小、积分时间更短、旋转速度更快[6]。这使得VGOS天线对引力形变不那么敏感[7]，可以在单位时间内进行更多的观测且观测值的精确度更高。2019—2024年期间VGOS观测数据的时延拟合后残差加权均方根的平均值为16.77 ps，显著优于同时段传统S/X VLBI测量数据的30.97 ps。
2 参数解算与精度分析
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2.1 解算的基准与模型
地球自转参数包括反映地球自转轴相对于地壳运动的极移参数XP和YP、反映地球自转角不规则特征的UT1-UTC以及地球自转速率变化的日长变化参数(length of day, LOD)[8]。由于LOD可通过UT1-UTC序列转换得到，因此本次实验仅解算极移序列与UT1-UTC。本文在解算建模策略上基本遵循IVS构建ITRF2020的分析指南。解算基准采用国际地球参考框架ITRF2020和国际天球参考框架ICRF3，岁差/章动模型为IAU2006/2000A，对流层映射函数选取VMF3模型，并增加了对流层天顶(0.25~1 h)和梯度延迟(1~6 h)的分辨率，以利用单位时间内更多的观测数据。电离层延迟信息由观测文件读取，射电源位置的先验值取自IVS发布的结果。选用ITRF2020作为台站先验坐标和速度，数据解析引入了固体潮汐、海洋潮汐、射电望远镜热形变修正、大气潮负荷、相对论延迟等影响因子。
2.2 精度评价体系
将由VGOS观测资料解算的地球自转参数序列表示为ERPVGOS，ERPVGOS包括极移序列VGOS(XP)、VGOS(YP)，地球自转角不规则特征参数VGOS(UT1-UTC)序列；将由传统S/X频段VLBI观测资料解算的地球自转参数序列表示为ERPS/X VLBI，ERPS/X VLBI包括极移序列S/X VLBI(XP)、S/X VLBI(YP)以及地球自转角不规则特征参数S/X VLBI(UT1-UTC)序列；IERS发布的EOP 14 C04序列表示为ERPIERS。精度评价体系包括：1)差值比较。将ERPIERS序列与ERPVGOS序列、ERPS/X VLBI序列作差，分析整个同步对比实验数据解算结果的稳定性和系统误差情况；2)加权均方根(weighted root mean square，WRMS)统计。分别统计2019—2023年ERPIERS序列与ERPVGOS序列、ERPS/X VLBI序列平均误差、加权均方根[9]，对比分析ERPVGOS序列和ERPS/X VLBI序列的精度差异。设分析的实验数据为n，加权均方根的计算方式如下：
$\left\{\begin{array}{l}\mathrm{WRMS}_{\mathrm{VGOS}}= \\\sqrt{\left(\sum\limits_1^n\left(\mathrm{ERP}_{\mathrm{VGOS}}-\mathrm{ERP}_{\mathrm{IERS}}\right)^2\right) / n} \\\mathrm{WRMS}_{\mathrm{S} / \mathrm{X} \mathrm{VLBI}}= \\\sqrt{\left(\sum\limits_1^n\left(\mathrm{ERP}_{\mathrm{S} / \mathrm{X} \mathrm{VLBI}}-\mathrm{ERP}_{\mathrm{IERS}}\right)^2\right) / n}\end{array}\right.$
2.3 实验结果分析
数据处理过程中使用了nuSolve、Calc/Solve等VLBI数据分析软件。由于VGOS台站的更大带宽和双线性极化信号链，致使VGOS实验数据处理带来了一些与传统S/X VLBI实验数据处理完全不同的新挑战(https://ivscc.gsfc.nasa.gov/publications/gm2014/019_Cappallo.pdf，https://ivscc.gsfc.nasa.gov/IVSAC/IVSACcontact.htm)。实验过程中通过重新构建Vex准备文件中的频带和信道等配置文件，使用DiFX2软件相关器完成VLBI数据的关联操作(https://www.haystack.mit.edu/geo/vlbi_td/BB/044.pdf，https://www.haystack.mit.edu/geo/vlbi_td/BB/044.pdf)。
由于不同观测数据解算的ERP序列历元时间不同，IERS EOP 14 C04序列为1962年至今每天24：00的计算结果，而VLBI观测文件并不严格以00:00作为起始时刻，在进行分析前，使用三次样条插值法获取同一历元下的ERP序列值进行比较。图 3为2019—2023年VGOS与传统X/S VLBI全球观测数据解算完成后的XP、YP、UT1-UTC序列与EOP 14 C04相应参数序列的比较结果。
由图 3可见，利用不同类型观测数据进行解算，未表现出明显的系统误差，XP与YP残差序列主要集中在-1~1 mas之间，UT1-UTC残差序列主要集中在-0.1~0.1 ms之间，整个同步对比实验数据解算结果较为稳定和可靠。总体而言，传统X/S VLBI的差值序列相对平缓，差值分布更小；VGOS解算序列则表现出一定的偏移，而且这种偏移在YP分量序列中表现更明显，而对于UT1-UTC序列的VGOS解算序列与传统X/S VLBI较为接近。进一步分析VGOS、S/X VLBI与IERS比较的平均误差、加权均方根，其统计结果见表 2和图 4。
图 4显示2019—2023年期间VGOS与传统S/X VLBI同步观测数据IERS 14 C04之间平均误差、加权均方根(WRMS)的差异。同样可以得出，通过VGOS解算的UT1-UTC精度略高，而且更稳定，但极移解算分量存在显著的偏移。可能的原因一是目前VGOS网络所包含的台站数量较少，在大多数VGOS测段的观测中，只有6~7个测站参与，而传统S/X VLBI测量的测段通常包含10个或者更多测站[10]；二是目前绝大部分VGOS测站都位于北半球，而传统S/X VLBI测站具有更好的全球分布(图 1)。
为了进一步研究VGOS测站数和测站分布对ERP解算的影响，对以并址站为核心的实验站观测数据进行处理分析。其中澳大利亚霍巴特站(测站名称：Hobart12，测站代码：Hb)作为目前VGOS网络唯一在南半球运行的测站，优化了VGOS网型结构。实验选取包括Hobart12测站参与的并址站测段，且台站数在10个以上的观测数据进行处理。并址站参与的VGOS测段表示为VGOS(Hb)，并使用与§2.1相同的数据处理方法进行处理，同样以EOP 14 C04序列作为基础序列进行比较。并址站参与的VGOS观测信息及解算结果见表 3，精度统计见表 4。
由表 4可见，用以并址站为核心的实验站的观测数据解算ERP结果的精度显著提高(图 5)。其平均误差精度大幅提升，加权均方根精度相对传统S/X VLBI，XP分量提高2.92倍，YP分量提高2.34倍，UT1-UTC提高1.99倍。尤其是极移分量精度的提高说明全球站点分布良好，特别是南半球测站的建立对提高精度有重要影响；而UT1-UTC增幅较小，也与目前VGOS全球测站东西分布优于南北分布一致。
此外，Hobart12测站虽然是VGOS网络测站，但其本质上是模仿传统的S/X模式运行的。唯一的区别在于，它记录的是双线性偏振信号，而不是传统S/X波段使用的右旋圆偏振信号。此外，其天线方位角的转动速率仅为6°/s，远低于VGOS预期设计的12°/s，这在一定程度上限制了VGOS观测数据的数量和拟合时延残差的精度。如果能够进一步优化VGOS网络的观测结构并改善台站设备状态，VGOS观测数据的解算精度仍有很大的提升空间。与传统S/X VLBI相比，VGOS通过强化自动化运行和远程控制功能，不仅提高了系统的响应速度，还降低了运行成本[11]。随着VGOS观测站网络的不断完善、观测频率的增加，以及数据处理方法的持续改进，VGOS数据在解算地球自转参数(ERP)方面的精度有望显著提升。
3 结语
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本文通过选取2019—2023年期间多基线组成的24 h VGOS观测和同步传统S频段和X频段为主的24 h VLBI观测数据进行解算，得到以下结论：
1) 在选取的实验数据时段，VGOS测段每次参与的台站数少于传统观测，但VGOS测段可以在单位时间内进行更多的观测，且观测值的精度更高。5 a期间VGOS观测数据的时延拟后残差加权均方根(WRMS)的平均值为16.77 ps，显著优于同时段传统S/X VLBI测量数据的30.97 ps。
2) 当前VGOS和传统S/X VLBI的全球网络站观测数据，在解算地球自转参数方面还存在差异。其中，VGOS解算ERP极移分量精度不如传统S/X VLBI，UT1-UTC精度与传统S/X VLBI测量相当。进一步选取以并址站为核心的实验站观测数据进行分析表明，VGOS测段解算ERP精度优于传统S/X VLBI测量。其中，XP分量提高2.92倍，YP分量提高2.34倍，UT1-UTC提高1.99倍。
由于当前VGOS参与测站数量较少且绝大部分VGOS测站都位于北半球，影响极移分量的精度。随着VGOS观测站网络的不断发展、观测频率的增加以及VGOS数据处理方法的不断改进，有望提供更高精度和准确性的ERP解算结果。

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doi: 10.14075/j.jgg.2024.09.436
  • 接收时间：2024-09-19
  • 首发时间：2026-10-29
  • 出版时间：2025-09-15
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红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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