Solving the latency problem in Real-time GNSS Precise Point Positioning using open source software
Metadatos
Mostrar el registro completo del ítemcomunitat-uji-handle:10234/158176
comunitat-uji-handle2:10234/71345
comunitat-uji-handle3:10234/141145
comunitat-uji-handle4:
TFG-TFMMetadatos
Título
Solving the latency problem in Real-time GNSS Precise Point Positioning using open source softwareAutoría
Tutor/Supervisor; Universidad.Departamento
Huerta Guijarro, Joaquín; Universitat Jaume I. Departament de Llenguatges i Sistemes InformàticsFecha de publicación
2020-03Editor
Universitat Jaume IResumen
Real-time Precise Point Positioning (PPP) can provide the Global Navigation Satellites
Systems (GNSS) users with the ability to determine their position accurately using
only one GNSS receiver.
The PPP solution ... [+]
Real-time Precise Point Positioning (PPP) can provide the Global Navigation Satellites
Systems (GNSS) users with the ability to determine their position accurately using
only one GNSS receiver.
The PPP solution does not rely on a base receiver or local GNSS network. However,
for establishing a real-time PPP solution, the GNSS users are required to receive the
Real-Time Service (RTS) message over the Network Transported of RTCM via
Internet Protocol (NTRIP). The RTS message includes orbital, code biases, and clock
corrections.
The GNSS users receive those corrections produced by the analysis center with some
latency, which degraded the quality of coordinates obtained through PPP. In this
research, we investigate the Support Vector Machine (SVR) and RandomForest (RF)
as machine learning tools to overcome the latency for clock corrections in the CLK11
and IGS03 products. A BREST International GNSS Services permanent station in
France selected as a case study. BNC software implemented in real-time PPP for
around three days. Our results showed that the RF method could solve the latency
problem for both IGS03 and CLK11. While SVR performed better on the IGS03 than
CLK11; thus, it did not solve the latency on CLK11. This research contributes to
establishing a simulation of real-time GNSS user who can store and predict clock
corrections accordingly to their current observed latency.
The self-assessment of the reproducibility level of this study has a rank one out of the
range scale from zero to three according to the criteria and classifications are done by
(Nüst et al., 2018). [-]
Palabras clave / Materias
Descripción
Treball de Final de Màster Universitari Erasmus Mundus en Tecnologia Geoespacial (Pla de 2013). Codi: SIW013. Curs acadèmic 2019-2020
Tipo de documento
info:eu-repo/semantics/masterThesisDerechos de acceso
info:eu-repo/semantics/openAccess
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