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Improving precise point positioning performance based on Prophet model

Precision point positioning (PPP) is widely used in maritime navigation and other scenarios because it does not require a reference station. In PPP, the satellite clock bias (SCB) cannot be eliminated by differential, thus leading to an increase in positioning error. The prediction accuracy of SCB h...

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Detalles Bibliográficos
Autores principales: Liao, Shujian, Yang, Chenbo, Li, Dengao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7815151/
https://www.ncbi.nlm.nih.gov/pubmed/33465150
http://dx.doi.org/10.1371/journal.pone.0245561
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author Liao, Shujian
Yang, Chenbo
Li, Dengao
author_facet Liao, Shujian
Yang, Chenbo
Li, Dengao
author_sort Liao, Shujian
collection PubMed
description Precision point positioning (PPP) is widely used in maritime navigation and other scenarios because it does not require a reference station. In PPP, the satellite clock bias (SCB) cannot be eliminated by differential, thus leading to an increase in positioning error. The prediction accuracy of SCB has become one of the key factors restricting positioning accuracy. Although International GNSS Service (IGS) provides the ultra-rapid ephemeris prediction part (IGU-P), its quality and real-time performance can not meet the practical application. In order to improve the accuracy of PPP, this paper proposes to use the Prophet model to predict SCB. Specifically, SCB sequence is read from the observation part in the ultra-rapid ephemeris (IGU-O) released by IGS. Next, the SCB sequence between adjacent epochs are subtracted to obtain the corresponding SCB single difference sequence. Then using the Prophet model to predict SCB single difference sequence. Finally, the prediction result is substituted into the PPP positioning observation equation to obtain the positioning result. This paper uses the final ephemeris (IGF) published by IGS as a benchmark and compares the experimental results with IGU-P. For the selected four satellites, compared with the results of the IGU-P, the accuracy of SCB prediction of the model in this paper is improved by about 50.3%, 61.7%, 60.4%, and 48.8%. In terms of PPP positioning results, we use Real-time kinematic (RTK) measurements as a benchmark in this paper. Positioning accuracy has increased by 26%, 35%, and 19% in the N, E, and U directions, respectively. The results show that the Prophet model can improve the performance of PPP.
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spelling pubmed-78151512021-01-27 Improving precise point positioning performance based on Prophet model Liao, Shujian Yang, Chenbo Li, Dengao PLoS One Research Article Precision point positioning (PPP) is widely used in maritime navigation and other scenarios because it does not require a reference station. In PPP, the satellite clock bias (SCB) cannot be eliminated by differential, thus leading to an increase in positioning error. The prediction accuracy of SCB has become one of the key factors restricting positioning accuracy. Although International GNSS Service (IGS) provides the ultra-rapid ephemeris prediction part (IGU-P), its quality and real-time performance can not meet the practical application. In order to improve the accuracy of PPP, this paper proposes to use the Prophet model to predict SCB. Specifically, SCB sequence is read from the observation part in the ultra-rapid ephemeris (IGU-O) released by IGS. Next, the SCB sequence between adjacent epochs are subtracted to obtain the corresponding SCB single difference sequence. Then using the Prophet model to predict SCB single difference sequence. Finally, the prediction result is substituted into the PPP positioning observation equation to obtain the positioning result. This paper uses the final ephemeris (IGF) published by IGS as a benchmark and compares the experimental results with IGU-P. For the selected four satellites, compared with the results of the IGU-P, the accuracy of SCB prediction of the model in this paper is improved by about 50.3%, 61.7%, 60.4%, and 48.8%. In terms of PPP positioning results, we use Real-time kinematic (RTK) measurements as a benchmark in this paper. Positioning accuracy has increased by 26%, 35%, and 19% in the N, E, and U directions, respectively. The results show that the Prophet model can improve the performance of PPP. Public Library of Science 2021-01-19 /pmc/articles/PMC7815151/ /pubmed/33465150 http://dx.doi.org/10.1371/journal.pone.0245561 Text en © 2021 Liao et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Liao, Shujian
Yang, Chenbo
Li, Dengao
Improving precise point positioning performance based on Prophet model
title Improving precise point positioning performance based on Prophet model
title_full Improving precise point positioning performance based on Prophet model
title_fullStr Improving precise point positioning performance based on Prophet model
title_full_unstemmed Improving precise point positioning performance based on Prophet model
title_short Improving precise point positioning performance based on Prophet model
title_sort improving precise point positioning performance based on prophet model
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7815151/
https://www.ncbi.nlm.nih.gov/pubmed/33465150
http://dx.doi.org/10.1371/journal.pone.0245561
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