Global Navigation Satellite Systems (GNSS) are nowadays widely used in several technical and scientific activities. Since the early stages of development (mid 1980 s), given the high level of accuracy achieved in determining the coordinates of the receiver, it became clear that the extensive deployment of GPS stations all over the world would have improved many tasks in geodesy and geodynamics. The use of GNSS signals is now not only limited to the estimation of the receiver's position, but it has eventually become a key instrument for ionospheric and tropospheric remote sensing studies, and for soil features (GNSS reflectometry). In particular, GNSS can be used to monitor the ionosphere at different time and space scales. On a global scale, GNSS signals are used to generate Global Ionosphere Maps (GIM) by measuring the total electron content from stations located around the world. On a regional scale, the same signals can be used to detect fast ionospheric disturbances, including those generated by natural hazards, such as tsunami and earthquakes. %For these reasons, real-time GNSS applications became particularly relevant in a number of different scientific fields. The Variometric Approach is a processing algorithm for GNSS observations which allow a GNSS receiver to provide valuable real-time information in a stand-alone operative mode. This approach is based on single time differences of suitable linear combinations of GNSS carrier-phase measurements, using a stand-alone GNSS receiver and standard GNSS broadcast products (orbits and clocks corrections) that are available in real-time. This thesis investigates the possibility to apply the Variometric Approach to the monitoring of the ionosphere, in order to detect in real-time ionospheric disturbances generated by tsunami. The first chapter of this thesis will serve as a preface to define fundamental concepts that we will refer to throughout the rest of this work. The rest of this thesis is divided into two main parts. In the first part (chapter~\ref{sec:VADASE}), we present some advances and applications of the VADASE (Variometric Approach for Displacements Analysis Standalone Engine) algorithm to estimate in real time ground velocities and displacements using stand-alone GNSS receivers. This algorithm was eventually appointed as an effective strategy to contribute to GNSS seismology. In this section we used the 2016 Meinong earthquake occurred in Taiwan as a case study and we estimated coseismic displacements and propagation properties of the surface waves in a real-time scenario using low-cost GNSS receivers. The second part of this work (chapters \ref{sec:VARION}, \ref{sec:rtscenario}, and \ref{sec:VARIONimpementation}) is devoted to a new GNSS processing algorithm, VARION (Variometric Approach for Real-Time Ionosphere Observation), which is capable of estimating changes in the ionosphere's Total Electron Content (TEC) using stand-alone GNSS receivers in real time. In chapter~\ref{sec:rtscenario}, the effectiveness of VARION was proven on the following study cases: 2012 Haida Gwaii earthquake and tsunami event, 2015 Chile earthquake and tsunami event, 2013 U.S. East Coast meteotsunami event, and 2017 Mexico tsunami and geomagnetic storm events. Finally, some conclusions and relevant prospects for future VARION developments are outlined. VARION may represent a significant contribution to science because the ionosphere is strongly coupled to the dynamics of the Earth's surface, neutral atmosphere, and geomagnetic field. In particular, these ionospheric perturbations can be used to detect in real time detection atmospheric gravity waves due to tsunamis. During the NASA funded GNSS Tsunami Early Warning System 2017 workshop held in Sendai, Japan, July 25-27 2017, the VARION algorithm was appointed as the first real-time GNSS tsunami tracking and warning system based upon NASA's Global Differential GPS system.

New applications and challenges of GNSS variometric approach / Savastano, Giorgio. - (2018 Feb 21).

New applications and challenges of GNSS variometric approach

SAVASTANO, GIORGIO
21/02/2018

Abstract

Global Navigation Satellite Systems (GNSS) are nowadays widely used in several technical and scientific activities. Since the early stages of development (mid 1980 s), given the high level of accuracy achieved in determining the coordinates of the receiver, it became clear that the extensive deployment of GPS stations all over the world would have improved many tasks in geodesy and geodynamics. The use of GNSS signals is now not only limited to the estimation of the receiver's position, but it has eventually become a key instrument for ionospheric and tropospheric remote sensing studies, and for soil features (GNSS reflectometry). In particular, GNSS can be used to monitor the ionosphere at different time and space scales. On a global scale, GNSS signals are used to generate Global Ionosphere Maps (GIM) by measuring the total electron content from stations located around the world. On a regional scale, the same signals can be used to detect fast ionospheric disturbances, including those generated by natural hazards, such as tsunami and earthquakes. %For these reasons, real-time GNSS applications became particularly relevant in a number of different scientific fields. The Variometric Approach is a processing algorithm for GNSS observations which allow a GNSS receiver to provide valuable real-time information in a stand-alone operative mode. This approach is based on single time differences of suitable linear combinations of GNSS carrier-phase measurements, using a stand-alone GNSS receiver and standard GNSS broadcast products (orbits and clocks corrections) that are available in real-time. This thesis investigates the possibility to apply the Variometric Approach to the monitoring of the ionosphere, in order to detect in real-time ionospheric disturbances generated by tsunami. The first chapter of this thesis will serve as a preface to define fundamental concepts that we will refer to throughout the rest of this work. The rest of this thesis is divided into two main parts. In the first part (chapter~\ref{sec:VADASE}), we present some advances and applications of the VADASE (Variometric Approach for Displacements Analysis Standalone Engine) algorithm to estimate in real time ground velocities and displacements using stand-alone GNSS receivers. This algorithm was eventually appointed as an effective strategy to contribute to GNSS seismology. In this section we used the 2016 Meinong earthquake occurred in Taiwan as a case study and we estimated coseismic displacements and propagation properties of the surface waves in a real-time scenario using low-cost GNSS receivers. The second part of this work (chapters \ref{sec:VARION}, \ref{sec:rtscenario}, and \ref{sec:VARIONimpementation}) is devoted to a new GNSS processing algorithm, VARION (Variometric Approach for Real-Time Ionosphere Observation), which is capable of estimating changes in the ionosphere's Total Electron Content (TEC) using stand-alone GNSS receivers in real time. In chapter~\ref{sec:rtscenario}, the effectiveness of VARION was proven on the following study cases: 2012 Haida Gwaii earthquake and tsunami event, 2015 Chile earthquake and tsunami event, 2013 U.S. East Coast meteotsunami event, and 2017 Mexico tsunami and geomagnetic storm events. Finally, some conclusions and relevant prospects for future VARION developments are outlined. VARION may represent a significant contribution to science because the ionosphere is strongly coupled to the dynamics of the Earth's surface, neutral atmosphere, and geomagnetic field. In particular, these ionospheric perturbations can be used to detect in real time detection atmospheric gravity waves due to tsunamis. During the NASA funded GNSS Tsunami Early Warning System 2017 workshop held in Sendai, Japan, July 25-27 2017, the VARION algorithm was appointed as the first real-time GNSS tsunami tracking and warning system based upon NASA's Global Differential GPS system.
21-feb-2018
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1077041
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