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Remote Sensing
Volume 16
Issue 15
10.3390/rs16152739
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Open AccessTechnical Note
by Shuai Liu SciProfiles Scilit Preprints.org Google Scholar Yunbin Yuan SciProfiles Scilit Preprints.org Google Scholar Xiaosong Guo SciProfiles Scilit Preprints.org Google Scholar Kezhi Wang SciProfiles Scilit Preprints.org Google Scholar Gongwei Xiao SciProfiles Scilit Preprints.org Google Scholar 
Shuai LiuYunbin YuanXiaosong GuoKezhi WangGongwei Xiao
1
The 54th Research Institute of CETC, Shijiazhuang 050081, China
2
State Key Laboratory of Geodesy and Earth’s Dynamics, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences, Wuhan 430071, China
3
School of Communications and Information Engineering (School of Artificial Intelligence), Xi’an University of Posts and Telecommunications, Xi’an 710121, China
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Author to whom correspondence should be addressed.
Remote Sens. 2024, 16(15), 2739; https://doi.org/10.3390/rs16152739
Submission received: 20 June 2024 / Revised: 18 July 2024 / Accepted: 25 July 2024 / Published: 26 July 2024
(This article belongs to the Special Issue Beidou/GNSS Positioning, Navigation and Timing: Methods and Technology (Second Edition))
Abstract
Precise point positioning (PPP) is a prevalent, high-precision spatial absolution positioning method, and its performance can be enhanced by ambiguity resolution (AR). To fulfill the growing need for high-precision positioning, we developed an open-source GNSS data processing package based on the decoupled clock model called Cube, which integrates decoupled clock offset estimation and precise point positioning with ambiguity resolution (PPP-AR). Cube is a secondary development based on RTKLIB. Besides the decoupled clock model, Cube can also estimate legacy clocks for the International GNSS Service (IGS), as well as clocks with satellite code bias extraction, and perform PPP-AR using the integer-recovered clock model. In this work, we designed satellite clock estimation and PPP-AR experiments with one week of GPS data to validate Cube’s performance. Results show that the software can produce high-precision satellite clock products and positioning results that are adequate for daily scientific study. With Cube, researchers do not need to rely on public PPP-AR products, and they can estimate decoupled clock products and implement PPP-AR anytime.
Keywords: open-source; Cube; precise point positioning; clock estimation; ambiguity resolution
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MDPI and ACS Style
Liu, S.; Yuan, Y.; Guo, X.; Wang, K.; Xiao, G. Cube: An Open-Source Software for Clock Offset Estimation and Precise Point Positioning with Ambiguity Resolution. Remote Sens. 2024, 16, 2739. https://doi.org/10.3390/rs16152739
AMA Style
Liu S, Yuan Y, Guo X, Wang K, Xiao G. Cube: An Open-Source Software for Clock Offset Estimation and Precise Point Positioning with Ambiguity Resolution. Remote Sensing. 2024; 16(15):2739. https://doi.org/10.3390/rs16152739
Chicago/Turabian Style
Liu, Shuai, Yunbin Yuan, Xiaosong Guo, Kezhi Wang, and Gongwei Xiao. 2024. "Cube: An Open-Source Software for Clock Offset Estimation and Precise Point Positioning with Ambiguity Resolution" Remote Sensing 16, no. 15: 2739. https://doi.org/10.3390/rs16152739
Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.
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MDPI and ACS Style
Liu, S.; Yuan, Y.; Guo, X.; Wang, K.; Xiao, G. Cube: An Open-Source Software for Clock Offset Estimation and Precise Point Positioning with Ambiguity Resolution. Remote Sens. 2024, 16, 2739. https://doi.org/10.3390/rs16152739
AMA Style
Liu S, Yuan Y, Guo X, Wang K, Xiao G. Cube: An Open-Source Software for Clock Offset Estimation and Precise Point Positioning with Ambiguity Resolution. Remote Sensing. 2024; 16(15):2739. https://doi.org/10.3390/rs16152739
Chicago/Turabian Style
Liu, Shuai, Yunbin Yuan, Xiaosong Guo, Kezhi Wang, and Gongwei Xiao. 2024. "Cube: An Open-Source Software for Clock Offset Estimation and Precise Point Positioning with Ambiguity Resolution" Remote Sensing 16, no. 15: 2739. https://doi.org/10.3390/rs16152739
Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.
Remote Sens., EISSN 2072-4292, Published by MDPI
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