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Assessment of the Improvement in Observation Precision of GNSS, SLR, VLBI, and DORIS Inputs from ITRF2014 to ITRF2020 Using TRF Stacking Methods | |
2024-04 | |
发表期刊 | REMOTE SENSING (IF:4.2[JCR-2023],4.9[5-Year]) |
ISSN | 2072-4292 |
EISSN | 2072-4292 |
卷号 | 16期号:7 |
发表状态 | 已发表 |
DOI | 10.3390/rs16071240 |
摘要 | International terrestrial reference frame (ITRF) input data, generated by Global Navigation Satellite Systems (GNSS), Satellite Laser Ranging (SLR), Very Long Baseline Interferometry (VLBI), and Doppler Orbitography and Radiopositioning integrated by satellite (DORIS) combination centers (CCs), are considered to be relatively high-quality and accurate solutions. Every few years, these input data are submitted to the three ITRS combination centers, namely Institut Géographique National (IGN), Deutsches Geodätisches Forschungsinstitut at the Technische Universität München (DGFI-TUM), and Jet Propulsion Laboratory (JPL), to establish a multi-technique combined terrestrial reference frame (TRF). Generally, these solutions have undergone three rounds of outlier removal: the first at the technique analysis centers during solution generations and the second during the technique-specific combination by the CCs; ITRS CCs then perform a third round of outlier removal and preprocessing during the multi-technique combination of TRFs. However, since the primary objective of CCs is to release the final TRF product, they do not emphasize the publication of analytical preprocessing results, such as the outlier rejection rate. In this paper, our specific focus is on assessing the precision improvement of ITRF input data from 2014 to 2020, which includes evaluating the accuracy of coordinates, the datum accuracy, and the precision of the polar motions, for all four techniques. To achieve the above-mentioned objectives, we independently propose a TRF stacking approach to establish single technical reference frameworks, using software developed by us that is different from the ITRF generation. As a result, roughly 0.5% or less of the SLR observations are identified as outliers, while the ratio of DORIS, GNSS, and VLBI observations are below 1%, around 2%, and ranging from 1% to 1.2%, respectively. It is shown that the consistency between the SLR scale and ITRF has improved, increasing from around −5 mm in ITRF2014 datasets to approximately −1 mm in ITRF2020 datasets. The scale velocity derived from fitting the VLBI scale parameter series with all epochs in ITRF2020 datasets differs by approximately 0.21 mm/year from the velocity obtained by fitting the data up to 2013.75 because of the scale drift of VLBI around 2013. The decreasing standard deviations of the polar motion parameter (XPO, YPO) offsets between Stacking TRFs and 14C04 (20C04) indicate an improvement in the precision of polar motion observations for all four techniques. From the perspective of the weighted root mean square (WRMS) in station coordinates, since the inception of the technique, the station coordinate WRMS of DORIS decreased from 30 mm to 5 mm for X and Y components, and 25 mm to 5 mm for the Z component; SLR WRMS decreased from 20 mm to better than 10 mm (X, Y and Z); GNSS WRMS decreased from 4 mm to 1.5 mm (X and Y) and 5 mm to 2 mm (Z); while VLBI showed no significant change. © 2024 by the authors. |
关键词 | Geodetic satellites Global positioning system Input output programs Statistics Dopple orbitography and radiopositioning integrated by satellite Doppler Global Navigation Satellite Systems International terrestrial reference frames Orbitography Quality assessment Satellite laser ranging Space geodesy Stackings Terrestrial reference frame Terrestrial reference frame stacking Very long baseline interferometry |
URL | 查看原文 |
收录类别 | SCI ; EI |
语种 | 英语 |
WOS研究方向 | Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology |
WOS类目 | Environmental Sciences ; Geosciences, Multidisciplinary ; Remote Sensing ; Imaging Science & Photographic Technology |
WOS记录号 | WOS:001201568600001 |
出版者 | Multidisciplinary Digital Publishing Institute (MDPI) |
EI入藏号 | 20241615921604 |
EI主题词 | Orbits |
EI分类号 | 405.3 Surveying ; 655.2 Satellites ; 723.1 Computer Programming ; 922.2 Mathematical Statistics |
原始文献类型 | Journal article (JA) |
引用统计 | 正在获取...
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文献类型 | 期刊论文 |
条目标识符 | https://kms.shanghaitech.edu.cn/handle/2MSLDSTB/364662 |
专题 | 物质科学与技术学院 物质科学与技术学院_特聘教授组_黄乘利组 物质科学与技术学院_博士生 |
通讯作者 | Huang, Chengli |
作者单位 | 1.Shanghai Astronomical Observatory, Chinese Academy of Sciences, Shanghai; 200031, China 2.School of Physical Science and Technology, ShanghaiTech University, Shanghai; 201210, China 3.CAS Key Laboratory of Planetary Sciences, Shanghai Astronomical Observatory, Chinese Academy of Sciences, Shanghai; 200031, China 4.School of Astronomy and Space Science, University of Chinese Academy of Sciences, Beijing; 100049, China |
第一作者单位 | 物质科学与技术学院 |
通讯作者单位 | 物质科学与技术学院 |
推荐引用方式 GB/T 7714 | Zhang, Jin,Huang, Chengli,Lian, Lizhen,et al. Assessment of the Improvement in Observation Precision of GNSS, SLR, VLBI, and DORIS Inputs from ITRF2014 to ITRF2020 Using TRF Stacking Methods[J]. REMOTE SENSING,2024,16(7). |
APA | Zhang, Jin,Huang, Chengli,Lian, Lizhen,&Zhang, Simeng.(2024).Assessment of the Improvement in Observation Precision of GNSS, SLR, VLBI, and DORIS Inputs from ITRF2014 to ITRF2020 Using TRF Stacking Methods.REMOTE SENSING,16(7). |
MLA | Zhang, Jin,et al."Assessment of the Improvement in Observation Precision of GNSS, SLR, VLBI, and DORIS Inputs from ITRF2014 to ITRF2020 Using TRF Stacking Methods".REMOTE SENSING 16.7(2024). |
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