Solving the latency problem in real-time GNSS precise point positioning using open source software

Dissertation submitted in partial fulfilment of the requirements for the degree of Master of Science in Geospatial TechnologiesReal-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)

An Integrated Transmission-Media Noise Calibration Software For Deep-Space Radio Science Experiments

The thesis describes the implementation of a calibration, format-translation and data conditioning software for radiometric tracking data of deep-space spacecraft. All of the available propagation-media noise rejection techniques available as features in the code are covered in their mathematical formulations, performance and software implementations. Some techniques are retrieved from literature and current state of the art, while other algorithms have been conceived ex novo. All of the three typical deep-space refractive environments (solar plasma, ionosphere, troposphere) are dealt with by employing specific subroutines. Specific attention has been reserved to the GNSS-based tropospheric path delay calibration subroutine, since it is the most bulky module of the software suite, in terms of both the sheer number of lines of code, and development time. The software is currently in its final stage of development and once completed will serve as a pre-processing stage for orbit determination codes. Calibration of transmission-media noise sources in radiometric observables proved to be an essential operation to be performed of radiometric data in order to meet the more and more demanding error budget requirements of modern deep-space missions. A completely autonomous and all-around propagation-media calibration software is a novelty in orbit determination, although standalone codes are currently employed by ESA and NASA. The described S/W is planned to be compatible with the current standards for tropospheric noise calibration used by both these agencies like the AMC, TSAC and ESA IFMS weather data, and it natively works with the Tracking Data Message file format (TDM) adopted by CCSDS as standard aimed to promote and simplify inter-agency collaboration

A new climatological electron density model for supporting space weather services

The ionosphere is the ionized part of the Earth atmosphere, ranging from about 60 km up to several Earth radii whereas the upper part above about 1000 km height up to the plasmapause is usually called the plasmasphere. We present a new three-dimensional electron density model aiming for supporting space weather services and mitigation of propagation errors for trans-ionospheric signals. The model is developed by superposing the Neustrelitz Plasmasphere Model (NPSM) to an ionosphere model composed of separate F and E-layer distributions. It uses the Neustrelitz TEC model (NTCM), Neustrelitz Peak Density Model (NPDM) and the Neustrelitz Peak Height Model (NPHM) for the total electron content (TEC), peak ionization and peak height information. These models describe the spatial and temporal variability of the key parameters as function of local time, geographic/geomagnetic location, solar irradiation and activity. The model is particularly developed to calculate the electron concentration at any given location and time in the ionosphere for trans-ionospheric applications and named as the Neustrelitz Electron Density Model (NEDM2020). A comprehensive validation study is conducted against electron density in-situ data from DMSP and Swarm, Van Allen Probes and ICON missions, and topside TEC data from COSMIC/FORMOSAT-3 mission, bottom side TEC data from TOPEX/Poseidon mission and ground-based TEC data from International GNSS Service (IGS) covering both high and low solar activity conditions. Additionally, the model performance is compared with the 3D electron density model NeQuick2. Our investigation shows that the NEDM2020 performs better than the NeQuick2 when compared with the in-situ data from Van Allen Probes and ICON satellites and TEC data from COSMIC and TOPEX/Poseidon missions. When compared with DMSP and IGS TEC data both NEDM2020 and NeQuick2 perform very similarly

Development of high-precision snow mapping tools for Arctic environments

Le manteau neigeux varie grandement dans le temps et l’espace, il faut donc de nombreux points d’observation pour le décrire précisément et ponctuellement, ce qui permet de valider et d’améliorer la modélisation de la neige et les applications en télédétection. L’analyse traditionnelle par des coupes de neige dévoile des détails pointus sur l’état de la neige à un endroit et un moment précis, mais est une méthode chronophage à laquelle la distribution dans le temps et l’espace font défaut. À l’opposé sur la fourchette de la précision, on retrouve les solutions orbitales qui couvrent la surface de la Terre à intervalles réguliers, mais à plus faible résolution. Dans l’optique de recueillir efficacement des données spatiales sur la neige durant les campagnes de terrain, nous avons développé sur mesure un système d’aéronef télépiloté (RPAS) qui fournit des cartes d’épaisseur de neige pour quelques centaines de mètres carrés, selon la méthode Structure from motion (SfM). Notre RPAS peut voler dans des températures extrêmement froides, au contraire des autres systèmes sur le marché. Il atteint une résolution horizontale de 6 cm et un écart-type d’épaisseur de neige de 39 % sans végétation (48,5 % avec végétation). Comme la méthode SfM ne permet pas de distinguer les différentes couches de neige, j’ai développé un algorithme pour un radar à onde continue à modulation de fréquence (FM-CW) qui permet de distinguer les deux couches principales de neige que l’on retrouve régulièrement en Arctique : le givre de profondeur et la plaque à vent. Les distinguer est crucial puisque les caractéristiques différentes des couches de neige font varier la quantité d’eau disponible pour l’écosystème lors de la fonte. Selon les conditions sur place, le radar arrive à estimer l’épaisseur de neige selon un écart-type entre 13 et 39 %. vii Finalement, j’ai équipé le radar d’un système de géolocalisation à haute précision. Ainsi équipé, le radar a une marge d’erreur de géolocalisation d’en moyenne <5 cm. À partir de la mesure radar, on peut déduire la distance entre le haut et le bas du manteau neigeux. En plus de l’épaisseur de neige, on obtient également des points de données qui permettent d’interpoler un modèle d’élévation de la surface solide sous-jacente. J’ai utilisé la méthode de structure triangulaire (TIN) pour toutes les interpolations. Le système offre beaucoup de flexibilité puisqu’il peut être installé sur un RPAS ou une motoneige. Ces outils épaulent la modélisation du couvert neigeux en fournissant des données sur un secteur, plutôt que sur un seul point. Les données peuvent servir à entraîner et à valider les modèles. Ainsi améliorés, ils peuvent, par exemple, permettre de prédire la taille, le niveau de santé et les déplacements de populations d’ongulés, dont la survie dépend de la qualité de la neige. (Langlois et coll., 2017.) Au même titre que la validation de modèles de neige, les outils présentés permettent de comparer et de valider d’autres données de télédétection (par ex. satellites) et d’élargir notre champ de compréhension. Finalement, les cartes ainsi créées peuvent aider les écologistes à évaluer l’état d’un écosystème en leur donnant accès à une plus grande quantité d’information sur le manteau neigeux qu’avec les coupes de neige traditionnelles.Abstract: Snow is highly variable in time and space and thus many observation points are needed to describe the present state of the snowpack accurately. This description of the state of the snowpack is necessary to validate and improve snow modeling efforts and remote sensing applications. The traditional snowpit analysis delivers a highly detailed picture of the present state of the snow in a particular location but lacks the distribution in space and time as it is a time-consuming method. On the opposite end of the spatial scale are orbital solutions covering the surface of the Earth in regular intervals, but at the cost of a much lower resolution. To improve the ability to collect spatial snow data efficiently during a field campaign, we developed a custom-made, remotely piloted aircraft system (RPAS) to deliver snow depth maps over a few hundred square meters by using Structure-from-Motion (SfM). The RPAS is capable of flying in extremely low temperatures where no commercial solutions are available. The system achieves a horizontal resolution of 6 cm with snow depth RMSE of 39% without vegetation (48.5% with vegetation) As the SfM method does not distinguish between different snow layers, I developed an algorithm for a frequency modulated continuous wave (FMCW) radar that distinguishes between the two main snow layers that are found regularly in the Arctic: “Depth Hoar” and “Wind Slab”. The distinction is important as these characteristics allow to determine the amount of water stored in the snow that will be available for the ecosystem during the melt season. Depending on site conditions, the radar estimates the snow depth with an RMSE between 13% and 39%. v Finally, I equipped the radar with a high precision geolocation system. With this setup, the geolocation uncertainty of the radar on average < 5 cm. From the radar measurement, the distance to the top and the bottom of the snowpack can be extracted. In addition to snow depth, it also delivers data points to interpolate an elevation model of the underlying solid surface. I used the Triangular Irregular Network (TIN) method for any interpolation. The system can be mounted on RPAS and snowmobiles and thus delivers a lot of flexibility. These tools will assist snow modeling as they provide data from an area instead of a single point. The data can be used to force or validate the models. Improved models will help to predict the size, health, and movements of ungulate populations, as their survival depends on it (Langlois et al., 2017). Similar to the validation of snow models, the presented tools allow a comparison and validation of other remote sensing data (e.g. satellite) and improve the understanding limitations. Finally, the resulting maps can be used by ecologist to better asses the state of the ecosystem as they have a more complete picture of the snow cover on a larger scale that it could be achieved with traditional snowpits

Beyond 100: The Next Century in Geodesy

This open access book contains 30 peer-reviewed papers based on presentations at the 27th General Assembly of the International Union of Geodesy and Geophysics (IUGG). The meeting was held from July 8 to 18, 2019 in Montreal, Canada, with the theme being the celebration of the centennial of the establishment of the IUGG. The centennial was also a good opportunity to look forward to the next century, as reflected in the title of this volume. The papers in this volume represent a cross-section of present activity in geodesy, and highlight the future directions in the field as we begin the second century of the IUGG. During the meeting, the International Association of Geodesy (IAG) organized one Union Symposium, 6 IAG Symposia, 7 Joint Symposia with other associations, and 20 business meetings. In addition, IAG co-sponsored 8 Union Symposia and 15 Joint Symposia. In total, 3952 participants registered, 437 of them with IAG priority. In total, there were 234 symposia and 18 Workshops with 4580 presentations, of which 469 were in IAG-associated symposia. ; This volume will publish papers based on International Association of Geodesy (IAG) -related presentations made at the International Association of Geodesy at the 27th IUGG General Assembly, Montreal, July 2019. It will include papers associated with all of the IAG and joint symposia from the meeting, which span all aspects of modern geodesy, and linkages to earth and environmental sciences. It continues the long-running IAG Symposia Series

Beyond 100: The Next Century in Geodesy

This open access book contains 30 peer-reviewed papers based on presentations at the 27th General Assembly of the International Union of Geodesy and Geophysics (IUGG). The meeting was held from July 8 to 18, 2019 in Montreal, Canada, with the theme being the celebration of the centennial of the establishment of the IUGG. The centennial was also a good opportunity to look forward to the next century, as reflected in the title of this volume. The papers in this volume represent a cross-section of present activity in geodesy, and highlight the future directions in the field as we begin the second century of the IUGG. During the meeting, the International Association of Geodesy (IAG) organized one Union Symposium, 6 IAG Symposia, 7 Joint Symposia with other associations, and 20 business meetings. In addition, IAG co-sponsored 8 Union Symposia and 15 Joint Symposia. In total, 3952 participants registered, 437 of them with IAG priority. In total, there were 234 symposia and 18 Workshops with 4580 presentations, of which 469 were in IAG-associated symposia. ; This volume will publish papers based on International Association of Geodesy (IAG) -related presentations made at the International Association of Geodesy at the 27th IUGG General Assembly, Montreal, July 2019. It will include papers associated with all of the IAG and joint symposia from the meeting, which span all aspects of modern geodesy, and linkages to earth and environmental sciences. It continues the long-running IAG Symposia Series

Design and performance of a GNSS single-frequency multi-constellation vector tracking architecture for urban environments

In the last decade, Global Navigation Satellites Systems (GNSS) have gained a significant position in the development of urban navigation applications and associated services. The urban environment presents several challenges to GNSS signal reception, such as multipath and GNSS Line-of-Sight (LOS) blockage, which are translated in the positioning domain in a decreased navigation solution accuracy up to the lack of an available position. For this matter, Vector Tracking (VT) constitutes a promising approach able to cope with the urban environment-induced effects including multipath, NLOS reception and signal outages. This thesis is particularly focused on the proposal and design of a dual constellation GPS + Galileo single frequency L1/E1 Vector Delay Frequency Lock Loop (VDFLL) architecture for the automotive usage in urban environment. From the navigation point of view, VDFLL represents a concrete application of information fusion, since all the satellite tracking channels are jointly tracked and controlled by the common navigation Extended Kalman filter (EKF). The choice of the dual-constellation single frequency vector tracking architecture ensures an increased number of observations and at the same time allowing the conservation of the low-cost feasibility criteria of the mobile user’s receiver. Moreover, the use of single frequency L1 band signals implies the necessity of taking into account the ionospheric error effect. In fact, even after the application of the ionosphere error correction models, a resultant ionospheric residual error still remains in the received observations. The originality of this work relies on the implementation of a dual-constellation VDFLL architecture, capable of estimating the ionosphere residual error present in the received observations. This dissertation investigates the VDFLL superiority w.r.t the scalar tracking receiver in terms of positioning performance and tracking robustness for a real car trajectory in urban area in the presence of multipath and ionosphere residual error

Methods for Improving Performance in Consumer Grade GNSS Receivers

Viimeisten kolmen vuosikymmenen aikana satelliittinavigointi on kehittynyt ammatti ja sotilaskäyttäjien tekniikasta kaikkien saatavilla olevaksi tekniikaksi. Varsinkin viimeisen 15 vuoden aikana, kun vastaanottimet alkoivat pienentyä ja halpenivat, on lisääntynyt määrä yrityksiä, jotka toimittavat GPS-laitteita satoihin erilaisiin sovelluksiin. Kaikille moderneille tekniikoille on myös tyypillistä, että tutkimukseen ja siihen liittyvään vastaanottimien kehittämiseen on käytetty valtavasti rahaa, mikä on johtanut huomattavaan parantumiseen vastaanottimen suorituskyvyssä. GPS-vastaanottimien kehitystyön lisäksi uusien maailmanlaajuisten satelliittinavigointijärjestelmien, kuten venäläisen GLONASS, kiinalaisen BeiDou- ja eurooppalaisen Galileo-järjestelmien käyttöönotto tarjoaa entistä enemmän mahdollisuuksia suorituskyvyn parantamiseen. Sekä GPS että nämä uudet järjestelmät ovat myös ottaneet käyttöön uudentyyppisiä signaalirakenteita, jotka voivat tarjota parempilaatuisia havaintoja ja siten parantaa kaikkien vastaanottimien suorituskykyä. Lopuksi menetelmät, kuten PPP ja RTK, jotka aiemmin olivat varattu ammattikäyttäjille, ovat tulleet kuluttajamarkkinoille mahdollistaen ennennäkemättömän suorituskyvyn jokaiselle satelliittinavigointivastaanottimien käyttäjälle. Tässä opinnäytetyössä arvioidaan tämän kehityksen vaikutusta sekä suorituskykyyn että vastaanottimen arkkitehtuuriin. Työssä esitellään yksityiskohtaisesti FGI:ssä kehitetyn ohjelmistopohjaisen vastaanottimen, FGI-GSRx:n. Tämän vastaanottimen avulla on työssä arvioitu miten sekä uudet konstellaatiot että uudet nykyaikaiset signaalit ja niitten seurantamenetelmät vaikuttavat suorituskykyyn ja vastaanotin arkkitehtuuriin. Tämän lisäksi on arvioitu PPP- ja RTK-tarkkuuspaikannusmenetelmien vaikutus FinnRefCORS-verkkoa käyttäen useiden erityyppisten vastaanottimien kanssa, mukaan lukien kuluttajalaatuiset vastaanottimet. Tulokset osoittavat, että enemmän konstellaatioita ja signaaleja käytettäessä paikannusratkaisun tarkkuus paranee 3 metristä 1,4 metriin hyvissä olosuhteissa ja yli 10-kertaiseksi tiheästi rakennetuissa kaupungeissa, jossa käytettävissä olevien signaalien määrä kasvaa kertoimella 2 käytettäessä kolmea konstellaatiota. Uusia moderneja modulaatiotekniikoita, kuten BOC-modulaatiota, käytettäessä tulokset osoittavat Galileo-ratkaisun tarkkuuden paranevan lähes 25%:lla ja esitelty uusi signaalinkäsittelymenetelmä lisää tällaisen tarkkuuden saatavuutta 50%:sta lähes 100%:iin. Lopuksi tarkkuuspaikannusmenetelmien tulokset osoittavat, että 15 cm:n tarkkuus on saavutettavissa, mikä on merkittävä parannus verrattuna 1,4 metrin tarkkuuteen. Näiden parannusten saavuttamiseksi on olennaista, että itse vastaanotin on mukautettu hyödyntämään näitä uusia signaaleja ja konstellaatioita. Tämä tarkoittaa, että nykyaikaisten kuluttajamarkkinoiden vastaanottimien suunnittelu on haastavaa ja monissa tapauksissa ohjelmistopohjainen vastaanotin olisi parempi ja halvempi valinta kuin uusien mikropiirien kehittäminen.For the last three decades, satellite navigation has evolved from being a technology for professional and military users to a technology available for everyone. Especially during the last 15 years, since the receivers started getting smaller and cheaper, there has been an increasing number of companies delivering Global Positioning System (GPS) enabled devices for hundreds of different kind of applications. Typical for any modern technology, there has also been an enormous amount of money spent on research and accompanied receiver development resulting in an immense increase in receiver performance. In addition to the development efforts on GPS receivers the introduction of new global navigation satellite systems such as the Russian Globalnaja Navigatsionnaja Sputnikovaja Sistema (GLONASS), the Chinese BeiDou, and the European Galileo systems offers even more opportunities for improved performance. Both GPS and these new systems have also introduced new types of signal structures that can provide better quality observations and even further improve the performance of all receivers. Finally, methods like Precise Point Positioning (PPP) and Real Time Kinematic (RTK) that earlier were reserved for professional users have entered into the consumer market enabling never before seen performance for every user of satellite navigation receivers. This thesis will assess the impact of this development on both performance as well as on receiver architecture. The design of the software defined receiver developed at FGI, the FGI-GSRx, is presented in detail in this thesis. This receiver has then been used to assess the impact of using multiple constellations as well as new novel signal processing methods for modern signals. To evaluate the impact of PPP and RTK methods the FinnRef Continuously Operating Reference Station (CORS) network has been used together with several different types of receivers including consumer grade off the shelf receivers. The results show that when using more constellations and signals the accuracy of the positioning solution improves from3 meters to 1.4 meters in open sky conditions and by more than a factor 10 in severe urban canyons. For severe urban canyons the available also increases by a factor 2 when using three constellations. When using new modern modulation techniques like high order BOC results show an accuracy improvement for a Galileo solution of almost 25 % and the presented new signal processing method increase the availability of such an accuracy from 50 % to almost 100 %. Finally, results from precise point positioning methods show that an accuracy of 15 cm is achievable, which is a significant improvement compared to an accuracy of 1.4 m for a standalone multi constellation solution. To achieve these improvements, it is essential that the receiver itself is adapted to make use of these new signals and constellations. This means that the design of modern consumer market receivers is challenging and in many cases a software define receiver would be a better and cheaper choice than developing new Application Specific Integrated Circuit (ASIC)’s

Monitoring and Prediction of Severe Weather Phenomena through GNSS Meteorology

While primary use of Global Navigation Satellite System (GNSS) is positioning, navigation, and timing (PNT), various GNSS applications have emerged over the past decades that includes GNSS meteorology. GNSS meteorology is the remote sensing of the atmospheric constituents in the neutral atmosphere – mostly in the troposphere - using GNSS to deliver information about the state of atmosphere. Precipitable water vapor (PWV) is the total amount of water vapor in a column of air above the earth surface that varies rapidly with short temporal and spatial-scale during severe meteorological phenomena. The amount of PWV contained in the neutral atmosphere can be retrieved from GNSS signals received by ground-based GNSS observations. GNSS is an excellent tool where it is not affected by weather conditions (e.g., presence of clouds, which derive a challenge to traditional weather monitoring technologies). Another benefit of GNSS is the data availability and accessibility. This dissertation focuses on developing a PWV prediction model using GNSS observations to monitor and forecast the path of severe precipitations induced by hurricanes. By using the GNSS-derived PWV and meteorological variables, the trend of the water vapor distribution is determined for the time frames of before, during, and after the severe precipitation. For each time frame a unique prediction model is developed suing a principle component regression (PCR). The developed model can forecast the severe precipitation track induced by a hurricane up to 24 hours in advance. In this dissertation the prediction models are examined using a proposed statistical model for different types of hurricanes. The case studies are: 1) Hurricane Mathew in 2016, 2) Hurricane Harvey in 2017, 3) Hurricane Irma in 2017, and 4) Hurricane Florence in 2018. In each hurricane case study the patterns of the GNSS-derived PWV fluctuations are analyzed. In particular, a sudden and sharp increment in the PWV followed by sharp descending trends was observed a few hours prior to the onset of precipitation. Also, the predicted PWV rate of change is dramatically increased prior to a severe precipitation. Moreover, in each case study, the probability of precipitation rapidly increased when the PWV reached a threshold in the range of 50 mm to 55 mm. The threshold is determined by analyzing the correlation between PWV fluctuations and occurrence of rainfall during the hurricane lifetime. The threshold is applied for classification of prediction models into the “right before”, “during” and “right after” models based on the hurricane development stage. It should be emphasized that this study specially focuses on “right before” model, which is the most useful model to analyze the movement of hurricane. The proposed method was validated by analyzing the distribution pattern of the predicted PWV residual, its magnitude, and the actual observed PWV in the test site. For a robust analysis considering the uncertainty from the measurement noise and other error sources in the GNSS-derived PWV, the prediction residual at multiple sites in a local area are evaluated within the grids in the test area. The grid size is determined with the consideration of the test site and the geometric distribution of available CORS. The high probably location of heavy precipitation location by the grid-based prediction well agreed with the observed rain pattern that can be used for predicting the hurricane path. In addition, the negative correlation between the residuals of PWV measurements to the prediction model and the magnitude of precipitation was revealed. It shows the magnitude of the predicted model residuals can be used for hurricane tracking and potentially applies to evaluate the storm intensity. This study demonstrates the feasibility of GNSS for monitoring severe precipitations and proves the effectiveness of the statistical model for forecasting the precipitation path during the hurricane that is potentially applied to a hazard early warning system

The ESPAS e-infrastructure

ESPAS provides an e-Infrastructure to support access to a wide range of archived observations and model derived data for the near-Earth space environment, extending from the Earth's middle atmosphere up to the outer radiation belts. To this end, ESPAS will serve as a central access hub for researchers who wish to exploit multi-instrument multipoint data for scientific discovery, model development and validation, and data assimilation, among others. Observation based and model enhanced scientific understanding of the physical state of the Earth's space environment and its evolution is critical to advancing space weather and space climate studies, two very active branches of current scientific research. ESPAS offers an interoperable data infrastructure that enables users to find, access, and exploit near-Earth space environment observations from ground-based and spaceborne instruments and data from relevant models, obtained from distributed repositories. In order to facilitate efficient user queries ESPAS allows a highly flexible workflow scheme to select and request the desired data sets. ESPAS has the strategic goal of making Europe a leading player in the efficient use and dissemination of near-Earth space environment information offered by institutions, laboratories and research teams in Europe and worldwide, that are active in collecting, processing and distributing scientific data. Therefore, ESPAS is committed to support and foster new data providers who wish to promote the easy use of their data and models by the research community via a central access framework. ESPAS is open to all potential users interested in near-Earth space environment data, including those who are active in basic scientific research, technical or operational development and commercial applications