Multi-GNSS Precise Point Positioning with Ambiguity Resolution Based on the Decoupled Clock Model

Ambiguity resolution (AR) can markedly enhance the precision of precise point positioning (PPP) and accelerate the convergence process. The decoupled clock model represents a pivotal approach for ambiguity resolution, yet current research on this topic is largely confined to GPS. Consequently, in this study, we extend the investigation of the decoupled clock model to multi-GNSS. Firstly, based on the conventional model, we derive the multi-GNSS decoupled clock estimation model and the precise point positioning with ambiguity resolution (PPP-AR) model. Secondly, we provide a detailed explanation of the estimation process for the multi-GNSS decoupled clock estimation. To validate the efficacy of the proposed model, we conduct multi-GNSS decoupled clock estimation and PPP-AR experiments using six days of observation data. The results demonstrate that the decoupled clocks of GPS, Galileo, and BDS-3 can all achieve high accuracy, thus fully meeting the requirement of ambiguity resolution. In terms of positioning performance, the joint three systems have higher positioning accuracy, reaching 3.10 cm and 6.13 cm in horizontal and vertical directions, respectively. Furthermore, the convergence time (CT) and time to first fix (TTFF) are shortened, to 23.13 min and 13.65 min, respectively. The experimental findings indicate that the proposed multi-GNSS decoupled clock model exhibits high precision and rapid positioning service capabilities.

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Publication Details

Journal
Remote Sensing
Published
2024-08-15
DOI
https://doi.org/10.3390/rs16162999
Citations
2
Primary Topic
GNSS positioning and interference
Type
article
Field-Weighted Citation Impact
2.60

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article

Multi-GNSS Precise Point Positioning with Ambiguity Resolution Based on the Decoupled Clock Model

Gongwei Xiao, Kezhi Wang, Shuai Liu, Yunbin Yuan et al.
2 citations
Remote Sensing
GNSS positioning and interference
2.60
article

Multi-GNSS Precise Point Positioning with Ambiguity Resolution Based on the Decoupled Clock Model

Gongwei Xiao, Kezhi Wang, Shuai Liu, Yunbin Yuan, Xiaosong Guo
article en
2 citations

Abstract

Ambiguity resolution (AR) can markedly enhance the precision of precise point positioning (PPP) and accelerate the convergence process. The decoupled clock model represents a pivotal approach for ambiguity resolution, yet current research on this topic is largely confined to GPS. Consequently, in this study, we extend the investigation of the decoupled clock model to multi-GNSS. Firstly, based on the conventional model, we derive the multi-GNSS decoupled clock estimation model and the precise point positioning with ambiguity resolution (PPP-AR) model. Secondly, we provide a detailed explanation of the estimation process for the multi-GNSS decoupled clock estimation. To validate the efficacy of the proposed model, we conduct multi-GNSS decoupled clock estimation and PPP-AR experiments using six days of observation data. The results demonstrate that the decoupled clocks of GPS, Galileo, and BDS-3 can all achieve high accuracy, thus fully meeting the requirement of ambiguity resolution. In terms of positioning performance, the joint three systems have higher positioning accuracy, reaching 3.10 cm and 6.13 cm in horizontal and vertical directions, respectively. Furthermore, the convergence time (CT) and time to first fix (TTFF) are shortened, to 23.13 min and 13.65 min, respectively. The experimental findings indicate that the proposed multi-GNSS decoupled clock model exhibits high precision and rapid positioning service capabilities.

Remote SensingVol. 16(16)
Chinese Academy of Sciences (CN), Institute of Geodesy and Geophysics (CN), Xi’an University of Posts and Telecommunications (CN)
Natural Science Foundation of Hebei Province, National Key Research and Development Program of China
Openalex Percentile: Top 9%
GNSS positioning and interference
2.60
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Multi-GNSS Precise Point Positioning with Ambiguity Resolution Based on the Decoupled Clock Model — Gongwei Xiao, Kezhi Wang, et al. · Remote Sensing (2024) | TGRS Research Map | TGRS