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The customary procedure to compute the rate of total electron content index (ROTI) presents some limitations when using the geometry-free (GF) combination of Global Positioning System (GPS) L1 and L2 carriers tracked by geodetic receivers. First, the effect of the tracking strategy implemented by each receiver manufacturer to obtain the L2 carrier from code-less observations. Second, the impact of frequent cycle slips on the L2 carrier. These limitations hinder the monitoring and characterization of ionospheric scintillation. To overcome them, the present study proposes the calculation of ROTI from the individual (uncombined) L1 carrier-phase, ROTIL1, using the Geodetic Detrending (GD) post-processing methodology, in contrast to the conventional GF combination, ROTIGF. The analysis of the entire year 2020 shows that those two aforementioned limitations produce inconsistent ROTIGF values measured by pairs of close receivers from different manufacturers. In contrast, the distribution of ROTIL1 values shows a full consistency between different receivers, being significantly less affected by cycle slips and allowing a valid and well-grounded identification of scintillation. The study concludes that ROTIL1, calculated using a 60 s window from geodetic receivers operating at 1 Hz, provides a robust tool to monitor and characterize ionospheric scintillation world-wide and regardless of the type of receiver. In particular, a ROTIL1 threshold of 1.8 TECU/min is established as the minimum level of detectable scintillation in 2020, a year of low solar activity. The most intense scintillation periods in high-latitude regions are statistically characterized by the newly proposed ROTIL1., This work was supported in part by MCIN/AEI/10.13039/501100011033/Fondo Europeo de Desarrollo Regional (FEDER), Unión Europea (UE), under Project CNS2022-135383 and Project PID2022-138485OB-I00; and in part by European Space Agency (ESA) through the Open Space Innovation Platform program under Contract 4000137762/22/NL/GLC/ov, Peer Reviewed, Postprint (published version)

Inertial measurement units (IMUs) are key components of various applications including navigation, robotics, aerospace, and automotive systems. IMU sensor characteristics have a significant impact on the accuracy and reliability of these applications. In particular, noise characteristics and bias stability are critical for proper filter settings to perform a combined GNSS/IMU solution. This paper presents an analysis based on the Allan deviation of different IMU sensors that correspond to different grades of micro-electromechanical systems (MEMS)-type IMUs in order to evaluate their accuracy and stability over time. The study covers three IMU sensors of different grades (ascending order): Rokubun Argonaut navigator sensor (InvenSense TDK MPU9250), Samsung Galaxy Note10 phone sensor (STMicroelectronics LSM6DSR), and NovAtel PwrPak7 sensor (Epson EG320N). The noise components of the sensors are computed using overlapped Allan deviation analysis on data collected over the course of a week in a static position. The focus of the analysis is to characterize the random walk noise and bias stability, which are the most critical for combined GNSS/IMU navigation and may differ or may not be listed in manufacturers’ specifications. Noise characteristics are calculated for the studied sensors and examples of their use in loosely coupled GNSS/IMU processing are assessed. This work proposes a structured and reproducible approach for working with sensors for their use in navigation tasks in combination with GNSS, and can be used for sensors of different levels to supplement missing or incorrect sensor manufacturers’ data., This research was funded by Rokubun S.L. and Universitat Politècnica de Catalunya with industrial PhD grant number 2020 DI 108 from the Generalitat de Catalunya; This research was partially funded by the Spanish Ministry of Science and Innovation and European Union FEDER through projects CNS2022-135383 and PID2022-138485OB-I00., Peer Reviewed, Postprint (published version)

Ionospheric disturbances induced by seismic activity have been studied in recent years by many authors, showing an impact both before and after the occurrence of earthquakes. In this study, the ionospheric scintillation produced by the 2021 La Palma volcano eruption is analyzed. The Cumbre Vieja volcano was active from 19 September to 13 December 2021, and many earthquakes of magnitude 3–4 were recorded, with some of them reaching magnitude 5. Three methods, GNSS reference monitoring, GNSS reflectometry (GNSS-R) from NASA CYGNSS, and GNSS radio occultation (GNSS-RO) from COSMIC and Spire constellations, are used to compare and evaluate their sensitivity as proxies of earthquakes associated with the volcanic eruption. To compare the seismic activity with ionospheric scintillation, seismic energy release, and 95th percentile of the intensity scintillation parameter (S4), measurements have been computed at 6 h intervals for the whole duration of the volcanic eruption. GNSS-RO has shown the best correlation between earthquake energy and S4, with values up to 0.09 when the perturbations occur around 18 h after the seismic activity. GNSS reference monitoring station data also show some correlation 18 h and 7–8 d after. As expected, GNSS-R is the one that shows the smallest correlation, as the ionospheric signatures get masked by the signature of the surface where the reflection is taking place. Additionally, the three methods show a smaller correlation during the week before earthquakes. Given the small magnitude of the seismic activity, the correlation is barely detectable in this situation, and thus would be difficult to use in any application to find earthquake proxies., This research was supported in part by grant PID2021-126436OB-C21 from the Programa Estatal para Impulsar la Investigación Científico-Técnica y su Transferencia, del Plan Estatal de Investigación Científica, Técnica y de Innovación 2021–2023 (Spain) and in part by the European Social Fund (ESF). GNSS-RO Spire data have been provided by the European Space Agency through the ESA TPM SPIRE project ID 67176., Peer Reviewed, Postprint (published version)

Tesi en modalitat de compendi de publicacions, (English) This document presents the collection of four manuscripts published during my Doctoral academic formation, which main goal has been the real-time implementation of tools to monitor the ionosphere using Global Navigation Satellite System (GNSS) signals. Despite the fact that there is a vast literature on ionospheric modelling, the state-of-the-art becomes narrow when referring to real-time developments, especially fulfilling precise requirements on accuracy, performance, coverage, and confidence in the generated products. The main contribution of this work to the scientific community is the deployment of ionospheric-related products to monitor in real-time the state of the ionosphere. The first and second publications targeted the implementation of a novel strategy based on a definition of a GNSS Solar Flare (SF) monitor to automatically confirm Solar Flare Effects (Sfe) in geomagnetism. In the first scientific article, it is inspected the methodology used to fine-tune (adapt) a SF monitor, working with an eleven years period of data to statistically correlate detected SF using GNSS signals with respect to SFe. The results demonstrated that the proposed GNSS Solar Flare monitor can confirm Sfe events when traditional Sfe detectors are not able to respond categorically. The second publication details the methodological approach for defining the proposed GNSS Solar Flare monitor, focusing on the theoretical formulation of the Slant Total Electron Content (STEC) obtained. The third contribution used GNSS signals to detect the presence of Medium Scale Travelling Ionospheric Disturbance (MSTID) within a network of permanent GNSS stations that provide the high-accuracy positioning service known as Network-Real-Time Kinematics (NRTK). The effects of a MSTID are characterized in terms of fluctuations in the electron density in the iono- sphere, experienced differently by each one of the GNSS stations used as reference receivers within the NRTK, and resulting in a d, (Español) Este documento se centra en la implementación de herramientas para monitorizar la ionosfera terrestre por medio del uso de señales GNSS. Si bien se puede encontrar una literatura bastante amplia sobre el modelado de la ionosfera, son reducidos los trabajos relacionados con aplicaciones en tiempo real, particularmente si se busca cumplir con requerimientos específicos vinculados con la precisión, el rendimiento, el cubrimiento y la certidumbre de los productos generados. La principal contribución de esta tesis doctoral es la generación en tiempo real de productos para monitorizar el estado de la ionosfera. Las primeras dos publicaciones se centran en el desarrollo de una nueva metodología fundamentada en un detector de Fulguraciones Solares (SF) basado en mediciones GNSS para la confirmación de los efectos de un SF (SFe) detectados por sensores geomagnéticos. En el primer artículo, se expone el procedimiento para el diseño y ajuste del detector GNSS de SF (GNSS-SF), empleando para ello un periodo de once años de datos con los cuales correlacionar estadísticamente SF detectados por medio del detector GNSS y los eventos SFe detectados en magnetismo. Los resultados demuestran que el detector GNSS-SF es capaz de confirmar eventos SFe cuando estos últimos no son categóricamente validados por los instrumentos magnéticos. La segunda publicación detalla el enfoque metodológico desarrollado para definir el detector GNSS-SF que se propone en el artículo. La tercera publicación emplea señales GNSS para detectar la presencia de perturbaciones de escala media que se desplazan en la ionosfera (MSTID) en una red de estaciones GNSS fijas que brindan servicios de posicionamiento muy preciso (NRTK). Los efectos de una MSTID pueden ser caracterizados por medio de la fluctuación en el contenido electrónico de la ionosfera, experimentado de manera diferente por cada una de las estaciones GNSS usadas como referencia dentro del servicio NRTK, ocasionando una degradación en el pos, Postprint (published version)

Existing climatological ionosphere models, for example, GISM, SCIONAV, WBMOD, and STIPEE, have known limitations that prevent their wide use. In the framework of ESA study “Radio Climatology Models of the Ionosphere: Status and Way Forward” their performance was assessed using experimental observations of ionospheric scintillation collected over the past years to evaluate their ability to properly support future missions, and eventually indicate their weaknesses for future improvements. Model limitations are more important in terms of the intensity scintillation parameter (S4). To improve them, the COSMIC model has been fit (scaling factor and offset) to the measured data, and it became the one better predicting the intensity scintillation in a statistical sense., This research was funded by the project “Radio Climatology Models of the Ionosphere: Status and Way Forward,” ESA/ESTEC, grant number 4000120868/17/NL/AF [https://nebula.esa.int/content/radio-climatology-models-ionosphere-status-and-way-forward]. Article processing charges were funded by the project “GENESIS: GNSS Environmental and Societal Missions – Subproject UPC,” AEI Grant PID2021-126436OB-C21., Peer Reviewed, Postprint (published version)

Ionospheric disturbances induced by seismic activity have been studied in recent years by many authors, showing an impact both before and after the occurrence of earthquakes. In this study, the ionospheric scintillation produced by the 2021 La Palma volcano eruption is analyzed. The Cumbre Vieja volcano was active from 19 September to 13 December 2021, and many earthquakes of magnitude 3–4 were recorded, with some of them reaching magnitude 5. Three methods, GNSS reference monitoring, GNSS reflectometry (GNSS-R) from NASA CYGNSS, and GNSS radio occultation (GNSS-RO) from COSMIC and Spire constellations, are used to compare and evaluate their sensitivity as proxies of earthquakes associated with the volcanic eruption. To compare the seismic activity with ionospheric scintillation, seismic energy release, and 95th percentile of the intensity scintillation parameter (S4), measurements have been computed at 6 h intervals for the whole duration of the volcanic eruption. GNSS-RO has shown the best correlation between earthquake energy and S4, with values up to 0.09 when the perturbations occur around 18 h after the seismic activity. GNSS reference monitoring station data also show some correlation 18 h and 7–8 d after. As expected, GNSS-R is the one that shows the smallest correlation, as the ionospheric signatures get masked by the signature of the surface where the reflection is taking place. Additionally, the three methods show a smaller correlation during the week before earthquakes. Given the small magnitude of the seismic activity, the correlation is barely detectable in this situation, and thus would be difficult to use in any application to find earthquake proxies.