Article(id=1322566879873446332, tenantId=1146029695717560320, journalId=1281212831689347082, issueId=1322566845215912204, articleNumber=null, orderNo=null, doi=10.14075/j.jgg.2025.03.077, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=research-article, receivedDate=1741708800000, receivedDateStr=2025-03-12, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1793254116265, onlineDateStr=2026-10-29, pubDate=1771084800000, pubDateStr=2026-02-15, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1793254116265, onlineIssueDateStr=2026-10-29, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1793254116265, creator=13701087609, updateTime=1793254116265, updator=13701087609, issue=Issue{id=1322566845215912204, tenantId=1146029695717560320, journalId=1281212831689347082, year='2026', volume='46', issue='2', pageStart='139', pageEnd='261', issueExtLink='null', onlineDate='null', pubDate='1771084800000', pubDateStr='2026-02-15', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1793254108003, creator='13701087609', updateTime=1793254108003, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext=null, issueFiles=null, downloadFileDto=null}, startPage=220, endPage=226, ext={EN=ArticleExt(id=1322566881437921726, articleId=1322566879873446332, tenantId=1146029695717560320, journalId=1281212831689347082, language=EN, title=Performance Evaluation of Ionospheric Correction Models in China, columnId=null, journalTitle=Journal of Geodesy and Geodynamics, columnName=null, runingTitle=null, highlight=null, articleAbstract=

Using 60 days of observational data from 233 monitoring stations of the crustal movement observation network of China (CMONOC) in 2023, the ionospheric delay modeling accuracy and standard point positioning (SPP) accuracy of BDGIM, Klobuchar, NeQuickG and BDSBAS models are analyzed. The results show that the BDSBAS ionospheric correction has the highest accuracy, with the ionospheric delay residual error of 1.0 m and an average correction rate of 87% within the region, and 68% of the 3D positioning errors reaching 1.95 m. The NeQuickG and BDGIM models have similar performance, with the ionospheric delay residual error of 2.0 m and an average correction rate of 73%, and positioning accuracy of 2.59 m and 2.82 m, respectively. The Klobuchar model has a correction rate of 67% and a positioning accuracy of 4.35 m. For single frequency users within China, the BDSBAS ionospheric model is recommended as the first choice, followed by the BDGIM model, which has a relatively simpler algorithm and better accuracy.

, authors=Yi YANG1, 2, Qi LIU1, 2, 3, Li YANG1, 2, 3, *, Jinpeng REN1, 2, Kai ZHAO1, 2, Mengxiang WANG1, 2, Keqi SU1, 2, authorsList=Yi YANG, Qi LIU, Li YANG, Jinpeng REN, Kai ZHAO, Mengxiang WANG, Keqi SU, authorCompany=null, correspAuthors=Li YANG, authorNote=null, 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=1322566882847207879, articleId=1322566879873446332, tenantId=1146029695717560320, journalId=1281212831689347082, language=CN, title=中国区域广播电离层模型改正性能评估, columnId=1281909276545356011, journalTitle=大地测量与地球动力学, columnName=大地测量学, runingTitle=null, highlight=null, articleAbstract=

利用233个中国大陆构造环境监测网络(CMONOC)监测站2023年60 d的观测数据对BDGIM、Klobuchar、NeQuickG和BDSBAS模型电离层延迟建模精度和标准单点定位精度进行分析。结果表明, BDSBAS格网电离层改正精度最高, 电离层延迟残余误差为1.0 m, 区域内平均改正率达到87%, 68%的三维定位误差达到1.95 m; NeQuickG和BDGIM模型改正性能相当, 电离层延迟残余误差为2.0 m, 平均改正率达到73%, 定位精度分别为2.59 m和2.82 m; Klobuchar模型平均改正率为67%, 定位精度达到4.35 m。中国区域内单频用户可优先使用BDSBAS格网电离层模型, 其次可选择算法相对简单、精度较优的BDGIM模型。

, authors=杨艺1, 2, 刘琦1, 2, 3, 杨力1, 2, 3, *, 任金鹏1, 2, 赵凯1, 2, 王梦祥1, 2, 苏柯淇1, 2, authorsList=杨艺, 刘琦, 杨力, 任金鹏, 赵凯, 王梦祥, 苏柯淇, authorCompany=null, correspAuthors=杨力, authorNote=

杨艺, 硕士生, 主要研究方向为卫星导航与定位技术, E-mail:

, correspAuthorsNote=
杨力, 博士, 教授, 主要研究方向为大地测量与测量工程, E-mail:
, copyrightStatement=版权所有,未经授权,不得转载。, copyrightOwner=大地测量与地球动力学编辑部, extLink=null, articleAbsUrl=null, sourceXml=I9Q/e1pvfBJyGF4JB5dQWQ==, magXml=nWTi+/DGp6e4XCLtGFhbyA==, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=kzTmT5R2oKO23kw/ldynBQ==, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=WF2Qd2daP/wg2fjYPZSj9A==, mapNumber=null, fund=null)}, authors=[Author(id=1322566883371495890, tenantId=1146029695717560320, journalId=1281212831689347082, articleId=1322566879873446332, orderNo=0, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=yang_yi2419@163.com, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1322566883446993365, tenantId=1146029695717560320, journalId=1281212831689347082, articleId=1322566879873446332, authorId=1322566883371495890, language=EN, stringName=Yi YANG, firstName=Yi, middleName=null, lastName=YANG, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, 2, address=1 State Key Laboratory of Spatial Datum, Zhengzhou 450046, China
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杨艺, 硕士生, 主要研究方向为卫星导航与定位技术, E-mail:

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红色点为陆态网监测站点,蓝色点为GEO卫星

, figureFileSmall=gSNCI1deORKaCb4Kq/oVQQ==, figureFileBig=kzTmT5R2oKO23kw/ldynBQ==, tableContent=null), ArticleFig(id=1322566887985230348, tenantId=1146029695717560320, journalId=1281212831689347082, articleId=1322566879873446332, language=EN, label=Fig. 2, caption=Ionospheric delay residual errors of CMONOC stations under different ionosphere status using each models, figureFileSmall=nVYIotD9GptwHyG3peLA0g==, figureFileBig=HeapVswhOToJWWIqOJo2UA==, tableContent=null), ArticleFig(id=1322566888161391117, tenantId=1146029695717560320, journalId=1281212831689347082, articleId=1322566879873446332, language=CN, label=图2, caption=不同电离层状态下陆态网测站使用各模型的电离层延迟残余误差, figureFileSmall=nVYIotD9GptwHyG3peLA0g==, figureFileBig=HeapVswhOToJWWIqOJo2UA==, tableContent=null), ArticleFig(id=1322566888245277198, tenantId=1146029695717560320, journalId=1281212831689347082, articleId=1322566879873446332, language=EN, label=Fig. 3, caption=Ionospheric delay residual errors and correction rates during 60 days at CMONOC stations of each models, figureFileSmall=PXc2gIaWrviiv+OUEXLYow==, figureFileBig=1Kvlmkr85lre6LsecGLnTg==, tableContent=null), ArticleFig(id=1322566888329163279, tenantId=1146029695717560320, journalId=1281212831689347082, articleId=1322566879873446332, language=CN, label=图3, caption=采用不同模型时各陆态网测站60 d电离层延迟残余误差RMS值及改正率, figureFileSmall=PXc2gIaWrviiv+OUEXLYow==, figureFileBig=1Kvlmkr85lre6LsecGLnTg==, tableContent=null), ArticleFig(id=1322566888576627216, tenantId=1146029695717560320, journalId=1281212831689347082, articleId=1322566879873446332, language=EN, label=Fig. 4, caption=SPP errors of CMONOC stations using each ionospheric models, figureFileSmall=DoqzFPB6gp98Os+yzR+SzQ==, figureFileBig=jvxTbAWbtU+K+U7Er6Gatw==, tableContent=null), ArticleFig(id=1322566890250154515, tenantId=1146029695717560320, journalId=1281212831689347082, articleId=1322566879873446332, language=CN, label=图4, caption=采用不同电离层模型时各陆态网测站标准单点定位误差, figureFileSmall=DoqzFPB6gp98Os+yzR+SzQ==, figureFileBig=jvxTbAWbtU+K+U7Er6Gatw==, tableContent=null), ArticleFig(id=1322566890346623508, tenantId=1146029695717560320, journalId=1281212831689347082, articleId=1322566879873446332, language=EN, label=Tab. 1, caption=

RMS of ionospheric delay residual errors corrected by each models

, figureFileSmall=null, figureFileBig=null, tableContent=
模型名称区域平均RMS/m中纬度区域RMS/m低纬度区域RMS/m
平静期活跃期平静期活跃期平静期活跃期
BDSBAS0.871.150.721.051.221.82
NeQuickG1.772.401.442.282.502.67
BDGIM1.692.361.422.172.322.77
Klobuchar2.082.721.632.642.893.11
), ArticleFig(id=1322566890438898197, tenantId=1146029695717560320, journalId=1281212831689347082, articleId=1322566879873446332, language=CN, label=表1, caption=

各模型改正后的电离层延迟残余误差RMS值

, figureFileSmall=null, figureFileBig=null, tableContent=
模型名称区域平均RMS/m中纬度区域RMS/m低纬度区域RMS/m
平静期活跃期平静期活跃期平静期活跃期
BDSBAS0.871.150.721.051.221.82
NeQuickG1.772.401.442.282.502.67
BDGIM1.692.361.422.172.322.77
Klobuchar2.082.721.632.642.893.11
), ArticleFig(id=1322566890669584918, tenantId=1146029695717560320, journalId=1281212831689347082, articleId=1322566879873446332, language=EN, label=Tab. 2, caption=

RMS of ionospheric delay residual errors and correction rates corrected by each models

, figureFileSmall=null, figureFileBig=null, tableContent=
模型名称区域平均中纬度区域(30°~60°N)低纬度区域(0°~30°N)
RMS/m改正率/%RMS/m改正率/%RMS/m改正率/%
BDSBAS1.01870.91871.6089
NeQuickG2.02741.77752.5773
BDGIM2.07731.73752.6972
Klobuchar2.49672.24673.0567
), ArticleFig(id=1322566890753470999, tenantId=1146029695717560320, journalId=1281212831689347082, articleId=1322566879873446332, language=CN, label=表2, caption=

各模型改正后的电离层延迟残余误差RMS值及改正率

, figureFileSmall=null, figureFileBig=null, tableContent=
模型名称区域平均中纬度区域(30°~60°N)低纬度区域(0°~30°N)
RMS/m改正率/%RMS/m改正率/%RMS/m改正率/%
BDSBAS1.01870.91871.6089
NeQuickG2.02741.77752.5773
BDGIM2.07731.73752.6972
Klobuchar2.49672.24673.0567
), ArticleFig(id=1322566890820579864, tenantId=1146029695717560320, journalId=1281212831689347082, articleId=1322566879873446332, language=EN, label=Tab. 3, caption=

Positioning error statistics of CMONOC stations using each ionosphere models

, figureFileSmall=null, figureFileBig=null, tableContent=
模型全部测站误差/m中纬度测站误差/m低纬度测站误差/m
68%95%68%95%68%95%
BDSBAS1.955.591.713.493.208.72
NeQuickG2.598.172.185.934.1411.18
BDGIM2.828.392.406.274.6411.88
Klobuchar4.3510.983.859.115.5613.40
), ArticleFig(id=1322566890887688729, tenantId=1146029695717560320, journalId=1281212831689347082, articleId=1322566879873446332, language=CN, label=表3, caption=

采用不同电离层模型时陆态网测站定位误差统计

, figureFileSmall=null, figureFileBig=null, tableContent=
模型全部测站误差/m中纬度测站误差/m低纬度测站误差/m
68%95%68%95%68%95%
BDSBAS1.955.591.713.493.208.72
NeQuickG2.598.172.185.934.1411.18
BDGIM2.828.392.406.274.6411.88
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中国区域广播电离层模型改正性能评估
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杨艺 1, 2 , 刘琦 1, 2, 3 , 杨力 1, 2, 3, * , 任金鹏 1, 2 , 赵凯 1, 2 , 王梦祥 1, 2 , 苏柯淇 1, 2
大地测量与地球动力学 | 大地测量学 2026,46(2): 220-226
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大地测量与地球动力学 |大地测量学 2026 , 46 (2) : 220 -226
中国区域广播电离层模型改正性能评估
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杨艺1, 2 , 刘琦1, 2, 3, 杨力1, 2, 3, * , 任金鹏1, 2, 赵凯1, 2, 王梦祥1, 2, 苏柯淇1, 2
作者信息
  • 1 空间基准全国重点实验室, 郑州, 450046
  • 2 河南大学遥感与空间信息工程学院, 郑州, 450046
  • 3 河南省时空大数据产业技术研究院(河南大学), 郑州, 450046
通讯作者:
杨力, 博士, 教授, 主要研究方向为大地测量与测量工程, E-mail:
作者简介:

杨艺, 硕士生, 主要研究方向为卫星导航与定位技术, E-mail:

Performance Evaluation of Ionospheric Correction Models in China
Yi YANG1, 2 , Qi LIU1, 2, 3, Li YANG1, 2, 3, * , Jinpeng REN1, 2, Kai ZHAO1, 2, Mengxiang WANG1, 2, Keqi SU1, 2
Affiliations
  • 1 State Key Laboratory of Spatial Datum, Zhengzhou 450046, China
  • 2 School of Remote Sensing and Information Engineering, Henan University, Zhengzhou 450046, China
  • 3 Henan Industrial Technology Academy of Spatiotemporal Big Data (Henan University), Zhengzhou 450046, China
出版时间: 2026-02-15 doi: 10.14075/j.jgg.2025.03.077
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利用233个中国大陆构造环境监测网络(CMONOC)监测站2023年60 d的观测数据对BDGIM、Klobuchar、NeQuickG和BDSBAS模型电离层延迟建模精度和标准单点定位精度进行分析。结果表明, BDSBAS格网电离层改正精度最高, 电离层延迟残余误差为1.0 m, 区域内平均改正率达到87%, 68%的三维定位误差达到1.95 m; NeQuickG和BDGIM模型改正性能相当, 电离层延迟残余误差为2.0 m, 平均改正率达到73%, 定位精度分别为2.59 m和2.82 m; Klobuchar模型平均改正率为67%, 定位精度达到4.35 m。中国区域内单频用户可优先使用BDSBAS格网电离层模型, 其次可选择算法相对简单、精度较优的BDGIM模型。

电离层模型  /  BDGIM  /  Klobuchar  /  NeQuickG  /  BDSBAS  /  性能评估

Using 60 days of observational data from 233 monitoring stations of the crustal movement observation network of China (CMONOC) in 2023, the ionospheric delay modeling accuracy and standard point positioning (SPP) accuracy of BDGIM, Klobuchar, NeQuickG and BDSBAS models are analyzed. The results show that the BDSBAS ionospheric correction has the highest accuracy, with the ionospheric delay residual error of 1.0 m and an average correction rate of 87% within the region, and 68% of the 3D positioning errors reaching 1.95 m. The NeQuickG and BDGIM models have similar performance, with the ionospheric delay residual error of 2.0 m and an average correction rate of 73%, and positioning accuracy of 2.59 m and 2.82 m, respectively. The Klobuchar model has a correction rate of 67% and a positioning accuracy of 4.35 m. For single frequency users within China, the BDSBAS ionospheric model is recommended as the first choice, followed by the BDGIM model, which has a relatively simpler algorithm and better accuracy.

ionospheric model  /  BDGIM  /  Klobuchar  /  NeQuickG  /  BDSBAS  /  performance evaluation
杨艺, 刘琦, 杨力, 任金鹏, 赵凯, 王梦祥, 苏柯淇. 中国区域广播电离层模型改正性能评估. 大地测量与地球动力学, 2026 , 46 (2) : 220 -226 . DOI: 10.14075/j.jgg.2025.03.077
Yi YANG, Qi LIU, Li YANG, Jinpeng REN, Kai ZHAO, Mengxiang WANG, Keqi SU. Performance Evaluation of Ionospheric Correction Models in China[J]. Journal of Geodesy and Geodynamics, 2026 , 46 (2) : 220 -226 . DOI: 10.14075/j.jgg.2025.03.077
电离层总电子含量(TEC)随地球空间环境变化,会干扰全球导航卫星系统(GNSS)信号,是定位、导航和授时服务中最大的误差源之一[1]。在太阳活跃期电离层暴期间,由电离层延迟引起的GNSS信号延迟误差可达百米[2]。采用双频观测数据可消除电离层延迟的影响,但观测值双频无电离层组合会放大观测噪声[3],在电离层较为平静的状态下,基于电离层改正模型的标准单点定位(SPP)反而能够提供更为精确的定位结果[4]。
当前,GPS采用Klobuchar电离层模型(GPSK),该模型系数源自基于Bent模型的全球电离层延迟经验模型[5-7]。Galileo采用NeQuickG模型,该模型为三维电离层电子密度半经验模型,广播3个有效电离因子参数以代替F10.7参数,从而满足实时修正需求[8-9]。北斗区域导航卫星系统(BDS-2)采用Klobuchar模型的修改版本,广播8个模型参数,与Klobuchar相比,BDS-2 Klobuchar模型假设南、北半球电离层延迟对称,而Klobuchar模型未采用该假设,并且2个模型所使用的映射函数不同[10-11]。北斗全球导航卫星系统(BDS-3)采用北斗全球电离层延迟修正模型(BDGIM)[12-13],该模型包含9个广播参数和17个非广播参数。此外,BDSBAS[14-15]、WAAS[16]和EGNOS[17]增强系统也利用区域监测站实时生成电离层格网延迟并向用户播发,以提升单频用户的定位精度和完好性[18]。电离层延迟评估是将模型建模的电离层延迟与双频实测数据解算结果进行对比[19],定位性能评估则是利用模型修正电离层延迟后评估单频单点定位的精度[20]。
Li等[4]对5种广播电离层模型(GPSK、NTCMG、NEQG、BDSK和BDGIM)在电离层平静和扰动条件下的标准单点定位性能进行研究,结果显示, BDGIM模型在2种条件下的定位误差RMS值均低于其他模型,分别为1.62 m和3.14 m。朱永兴等[21]进一步研究表明,BDGIM模型精度为3.6 TECu,优于NeQuickG(4.4 TECu)和Klobuchar(5.7 TECu)模型。毛悦等[9]通过与IGS全球格网电离层模型进行对比,发现BDGIM模型与IGS模型的一致性优于3 TECu,改正率达到77%,同样优于其他模型。此外,金彪等[22]对WAAS和EGNOS电离层改正精度进行分析,结果表明, 二者的电离层延迟改正精度达到0.5 m。
本文利用233个中国大陆构造环境监测网络(CMONOC)监测站数据,对BDGIM、NeQuickG、Klobuchar及BDSBAS电离层模型在中国区域的服务性能进行详细研究,旨在为手机、航空等单频用户选择更精准的电离层改正模型提供参考。
GPS Klobuchar模型计算公式如下:
$\begin{gathered}\operatorname{ION}(t)= \\\left\{\begin{array}{c}A_1+A_2 \cos \frac{2 \pi}{A_4}\left(t-A_3\right), \left|t-A_3\right|<\frac{A_4}{4} \\A_1, \left|t-A_3\right| \geqslant \frac{A_4}{4}\end{array}\right.\end{gathered}$
$A_2=\left\{\begin{array}{c}\sum\limits_{n=0}^3 a_n \varnothing_m^n, A_2>0 \\0, A_2 \leqslant 0\end{array}\right.$
$A_4=\left\{\begin{array}{c}\sum\limits_{n=0}^3 b_n \varnothing_m^n, A_4 \leqslant 72\;000 \\72\;000, A_4>72\;000\end{array}\right.$
式中,ION(t)为垂直电离层延迟(VTEC);t为穿刺点的地方时,单位s;A1为夜间电离层延迟平均值,为5 ns;A3为模型中余弦曲线极点的时间,即地方时14:00,通常认为此时电子总量达到最大值;A2和A4分别为模型函数的幅值和周期;Øm为电离层穿刺点(IPP)处的地磁纬度,单位弧度;an和bn为Klobuchar模型的8个广播参数(各4个)。
NeQuickG是一种全球电离层电子密度分布模型,最初由国际电信联盟无线电通信部门(ITU-R)推荐用于电离层时延校正。该模型基于一维NeQuick模型,扩展为三维,以描述全球范围内的电离层电子密度分布。
NeQuickG模型所需要的外部文件为12个CCIR系数文件和地磁纬度文件,有效电离因子Az可以代替太阳活动参数,Az可通过a0、a1、a2三个参数计算得到,参数由导航电文提供,具体公式如下:
$A_z=a_0+a_1 \times \operatorname{modip}+a_2 \times \operatorname{modip}^2$
式中,modip为用户位置的地磁倾角;Az取值范围为0~400。
SBAS主要服务于国际民航系统,其中的单频增强服务是参照航空无线电技术委员会(RTCA),通过卫星向用户播发轨道钟差改正数、电离层格网改正数和完好性信息,以提高用户端的单频定位精度。与其他实时电离层模型不同的是,SBAS电离层格网将全球范围划分为11个格网带,并以5°×5°为间隔定义总计2 192个电离层格网点。SBAS直接向用户播发对应服务区域内的格网点上的VTEC,用户端通过将穿刺点周边有效格网点上的VTEC内插到穿刺点上,即可计算得到穿刺点处的VTEC。计算公式如下:
$\mathrm{ION}=\frac{\sum\limits_{j=1}^n \mathrm{VTEC}_{\mathrm{IGP}, j} \times w_j}{\sum\limits_{j=1}^n w_j}$
式中,VTECIGP, j为电离层格网点上的VTEC;wj为该格网点对应的权重,用户端算法中通常采用反距离加权法计算得到。
BDGIM模型以球谐函数为基础,该模型包括播发项和非播发项参数,其中播发项为9个模型参数,非播发项参数信息则固化于用户接收机端。BDGIM模型表达式为:
$\mathrm{ION}=M \frac{40.28 \times 10^{16}}{f^2}\left(A_0+\sum\limits_{i=1}^9 \alpha_i A_i\right)$
式中,M为投影函数;A0为计算得到的电离层延迟预报值,通过接收机内部的非播发参数计算得到;αi为广播星历播发的电离层参数;Ai为根据观测时刻和穿刺点经纬度计算得到的电离层函数值。
利用双频观测数据计算GPS L1频点伪距电离层延迟,表达式为[23]:
$I_{\mathrm{L} 1, \text { true }}=\frac{P_1-P_2+\tau_{\mathrm{r}}-\tau^{\mathrm{s}}}{1-\gamma}, \gamma=\frac{f_1^2}{f_2^2}$
式中,P1和P2分别为GPS载波L1和L2上平滑后的伪距观测值;τr和τs分别为接收机和卫星的硬件延迟;γ为比例系数;f1和f2分别为L1和L2载波的频率。卫星端硬件延迟采用欧洲定轨中心(CODE)发布的差分码偏差(DCB)产品进行改正。利用IGS全球测站和本文选用的测站数据进行全球电离层延迟建模。
SBAS播发格网点的电离层垂直延迟,用户电离层穿刺点处倾斜延迟可表示为:
$I_s=F_p \cdot \sum\limits_{i=1}^n W_i I_{v, i}$
式中,Is为穿刺点处电离层斜延迟;n为穿刺点处可用的电离层格网点数量;Iv, i为SBAS播发的格网点i的电离层垂直延迟;Wi为加权因子;Fp为映射函数,用于将电离层垂直延迟转换为斜延迟。加权因子和映射函数计算方法见参考文献[24]。NequickG、BDGIM及Klobuchar模型计算电离层延迟的方法可参考各系统发布的接口控制文件[7, 10, 12]。将电离层模型计算的电离层斜延迟与双频观测数据解算得到的真实电离层延迟进行对比得到建模误差,同时采用下式计算电离层改正率:
$c_{\text {rate}}=\frac{\left|I_{\text {model}}-I_{\mathrm{L} 1, \text {true}}\right|}{I_{\mathrm{L} 1, \text {true}}}$
式中,Imodel为使用模型计算的电离层延迟。为减小伪距噪声的影响,在利用双频观测数据解算电离层延迟时设置高度角为30°。
利用中国大陆构造环境监测网络(简称陆态网, CMONOC)监测站数据对BDS、GPS、Galileo广播电离层模型及BDSBAS播发的电离层改正数进行电离层改正精度和定位精度评估。本文共选用243个陆态网监测站数据,观测时段为2023年doy1—60,采样间隔为30 s。监测站存储的数据文件仅支持GPS和GLONASS,因此采用GPS观测数据对电离层模型服务性能进行分析。陆态网站点分布和BDSBAS GEO卫星位置如图 1所示。
电离层活动状态与地磁场有关[25],地磁活动情况通常用Dst和Kp指数[26]来衡量。Dst指数越小、Kp指数越大,表明电离层越活跃。F10.7指数可反映太阳射电通量的强度,根据中国气象标准,太阳活动水平低于80 sfu表示低太阳活动,80~150 sfu表示中等太阳活动,超过150 sfu表示高太阳活动。选取2023年doy44(Kp=1.0, Dst=2 nT, F10.7=184.4 sfu)电离层平静时段和doy58(Kp=6.3, Dst=-90 nT, F10.7=158.1 sfu)电离层活跃时段的观测数据分析不同电离层模型在不同电离层状态下的建模精度。首先利用测站双频观测数据及GPS卫星和测站的差分码偏差(DCB)计算卫星和测站路径上的电离层斜延迟,并将结果作为参考值;然后分别利用BDSBAS、NeQuickG、BDGIM和Klobuchar模型计算电离层斜延迟,将其与参考值进行对比,计算建模误差;最后统计各测站1 d内所有电离层延迟残余误差的均方根(RMS)值。
图 2为高太阳活动时期下电离层平静时段和电离层活跃时段各陆态网监测站使用不同模型时电离层延迟残余误差RMS值,具体统计值见表 1。可以看出,在电离层活跃时段各模型改正精度均有所降低,且以30°N为分界线,以北区域建模精度高于分界线以南区域,后续分析中分别称为中纬度区域(30°~60°N)和低纬度区域(0°~30°N)。所有模型中BDSBAS电离层精度最高,即使在电离层活跃时段,低纬度区域建模精度仍达到1.82 m,得益于其较大的信息播发带宽和实时更新的电离层改正参数。NeQuickG和BDGIM模型精度相当,Klobuchar模型精度最低,电离层活跃期低纬度区域改正精度为3.11 m。
对评估时段共60 d的数据进行统计,得到经各电离层模型改正后的电离层延迟残余误差及对应的电离层改正率,结果如图 3所示,具体统计值见表 2。
在评估时段内,BDSBAS中国区域电离层延迟残余误差RMS值达到1.0 m,改正率为87%,显示出良好的服务性能;NeQuickG和BDGIM中国区域电离层平均改正精度达到2.0 m,改正率达到73%,中纬度区域改正率达到75%;Klobuchar模型平均改正精度达到2.4 m,改正率为68%。尽管低纬度区域电离层较为活跃、电离层延迟较大,但由于各电离层模型均考虑了这一特性,且电离层延迟绝对值较大,因此低纬度和中纬度区域电离层改正率差异不明显。与§3.1结果类似,在中国区域内,NeQuickG和BDGIM模型服务性能相当。
分别利用4种电离层模型开展GPS标准单点定位,对定位精度进行分析。图 4为采用不同电离层模型时陆态网各测站的三维RMS定位误差,可以看出,低纬度区域和中纬度区域定位精度差异明显,受活跃电离层影响,低纬度区域定位精度较低;BDSBAS电离层模型改正精度显著优于其他3种模型;NeQuickG模型在中纬度区域与BDGIM模型精度相当,在低纬度区域定位精度略优;Klobuchar模型整体精度最低。
表 3为使用不同电离层模型时CMONOC测站整体三维位置误差及中纬度和低纬度区域测站位置误差。采用BDSBAS、NeQuickG、BDGIM和Klobuchar电离层模型时,全部测站68%的位置误差分别为1.95 m、2.59 m、2.82 m和4.85 m,显示出BDSBAS优秀的服务性能。NeQuick和BDGIM模型表现同样较为突出,相比于Klobuchar模型,定位精度分别提升40%和35%。相对于中纬度区域,低纬度区域测站定位误差明显偏大,即使采用BDSBAS电离层模型,定位误差也超过3.0 m。
定位误差受多种因素的影响,包括电离层延迟、对流层延迟、多路径效应、接收机噪声等,其中电离层延迟是GNSS信号传播过程中最主要的误差源之一。通过比较不同电离层模型的改正精度和定位精度,可以看出电离层改正精度对定位精度的影响。BDSBAS模型在电离层改正精度上表现最佳,其定位精度也相应最高; NeQuickG和BDGIM模型电离层改正精度相当,其定位精度也较为接近。这表明电离层改正精度的提高可以直接改善定位精度。
低纬度区域定位精度明显低于中纬度区域,这与电离层活动强度有关。低纬度区域电离层活动更为活跃,电离层延迟变化更为剧烈,导致电离层改正模型精度下降,从而影响定位精度。为应对该问题,可以考虑提高电离层模型的时空分辨率和引入机器学习算法。
本文基于中国大陆构造环境监测网络233个监测站数据,对BDSBAS、NeQuickG、BDGIM和Klobuchar四种电离层模型在中国区域的服务性能进行全面评估,得到以下结论:
1) BDSBAS在中国区域表现最为突出,其电离层改正精度最高,经改正后的电离层延迟残余误差仅为1.0 m,平均改正率高达87%。在定位精度方面,采用BDSBAS模型时,68%的三维位置误差达到1.95 m,显著优于其他模型。这表明BDSBAS能够有效改正电离层延迟,可为单频用户提供高精度的定位服务。
2) NeQuickG和BDGIM模型在中国区域的改正性能相当。经改正后,两者的电离层延迟残余误差均为2.0 m,平均改正率达到73%。在定位精度方面,NeQuickG和BDGIM三维位置误差分别达到2.59 m和2.82 m。尽管两者精度略低于BDSBAS,但可提供相对简单且精度较优的解决方案,适用于对定位精度要求较高但BDSBAS信号覆盖不佳或无法使用的场景。
3) Klobuchar模型改正精度相对较低,但其电离层改正率仍达到67%,三维定位精度为4.35 m。表明Klobuchar模型在某些对精度要求不高的场景中仍具有应用价值,如部分物联网设备或低成本导航终端。
对于中国区域的GNSS单频用户,优先推荐使用BDSBAS电离层改正模型,该模型能够提供优于2.0 m的三维位置精度,满足大多数高精度应用的需求。其次,BDGIM模型是一个可靠的选择,其精度接近NeQuickG,且模型复杂度适中,易于实现。对于资源有限或对定位精度要求稍低的用户,BDGIM能够在保证一定精度的同时提供更高效的计算。
  • 国家自然科学基金(424040039)
  • 中国博士后科学基金(2023M730943)
  • 中国博士后科学基金(2024T170220)
  • 河南省科协青-人才托举工程(2024HYTP027)
  • 河南省自然科学基金(242300421643)
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2026年第46卷第2期
33
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doi: 10.14075/j.jgg.2025.03.077
  • 接收时间:2025-03-12
  • 首发时间:2026-10-29
  • 出版时间:2026-02-15
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  • 收稿日期:2025-03-12
基金
国家自然科学基金(424040039)
中国博士后科学基金(2023M730943)
中国博士后科学基金(2024T170220)
河南省科协青-人才托举工程(2024HYTP027)
河南省自然科学基金(242300421643)
作者信息
    1 空间基准全国重点实验室, 郑州, 450046
    2 河南大学遥感与空间信息工程学院, 郑州, 450046
    3 河南省时空大数据产业技术研究院(河南大学), 郑州, 450046

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杨力, 博士, 教授, 主要研究方向为大地测量与测量工程, E-mail:
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2种不同金属材料的力学参数
科
Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)
属
Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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