Atmospheric water vapour plays a crucial role in the climate system. It is not only a strong greenhouse gas, but also affects many atmospheric processes such as the formation of clouds and precipitation. Water vapour is directly related to changes in temperature, as described by the Clausius Clapeyron relation. Analysing how water vapour changes in time is therefore important in a warming climate.

We asses changes of integrated water vapour (IWV) over Bern, Switzerland, by analysing data from a tropospheric water radiometer (TROWARA). We compared TROWARA data to reanalysis data from the Modern-Era Retrospective analysis for Research and Applications (MERRA2). Further, the data are compared to surrounding ground stations of the Global Navigation Satellite System (GNSS), which are part of the Automated GNSS Network for Switzerland (AGNES). We observe that the different datasets generally agree well, with differences within 10%.

We determined IWV trends of almost 25 years of data and found trends between 1 and 6% per decade. Trend differences depending on seasonal and diurnal cycle are also presented, with slightly higher trends in spring and autumn. Further we found an altitude dependence of the trends, with larger trends for GNSS stations that lie at higher altitudes.

Our IWV trends are generally consistent with observed temperature changes. This confirms the positive temperature-water vapour feedback in a warming climate. However, we observe that not all data sets show trends that are significantly different from zero at 95% confidence interval. This insignificance of trends for some datasets emphasizes the need to continue to measure water vapour, with the aim to obtain stable long-term time series and to better understand water vapour feedbacks in a changing climate. GNSS data is of high interest for this endeavour due to its measurement continuity and its good spatial coverage.

Besides antenna phase center corrections (PCC) for carrier phase measurements, which have to be considered for precise GNSS application, also codephase variations (CPV) exist. These are antenna dependent delays of the code which vary with azimuth and elevation. Such variations are not provided operationally in the antenna exchange format (ANTEX) at the moment. Previous studies in our working group show, that CPV should be taken into account when using code-carrier combination. Depending on the antenna type they can amount up to some dm.
At Institut für Erdmessung (IfE), a concept to determine the CPV has been established. This procedure uses a robot that rotates and tilts the antenna under test precisely in the field. Real world modulated signals from the satellites are used, which is challenging in anechoic chamber procedures. Time differenced single differences are used to estimate PCC and CPV as spherical harmonics (8,8) in a post-processing approach.
In this contribution we present the concept CPV of Galileo signals for several kinds of receiving antennas (mass market and high grade). In addition, we discuss the repeatability and stability of CPV for those antenna. Typical values of the CPV reaches up to 500 mm. The RMS of patterns resulting from multiple calibrations are 80 mm for Galileo C1X and 48 mm for GPS C1C.

With the recent addition of GALILEO, four fully operational GNSS (Global Navigation Satellite System) are available nowadays, increasing the number of navigation satellites orbiting around the globe to more than 70. Thanks to different projects, such as the Multi-GNSS Experiment (MGEX) from the International GNSS Service (IGS), a global network of multi-GNSS receivers is available for the scientific community. These initiatives have shown great improvements for different solutions, such as Positioning, Navigation and Timing (PNT) applications and Earth monitoring techniques. Many GNSS precise positioning algorithms, such as Precise Point Positioning (PPP), rely on precise ionospheric corrections to calculate the position. In this paper, a multi-GNSS based ionospheric sensing method will be described. The imaging technique called Computerised Ionospheric Tomography (CIT) uses GNSS dual frequency observations to calculate the total electron content (TEC) from each satellite to the receiver path, which are used to create three-dimensional electron density images.
One of the key issues of GPS ionospheric tomography is the lack of data due to poor satellite and receiver coverage over the area under study. With the addition of GLONASS and GALILEO constellations into the ionospheric imaging algorithm, this problem is reduced. In this paper real data from both geomagnetically calm and disturbed days is used to assess the method. Reconstructions using receivers distributed all over the globe will be compared to regional data and maps from North America, South America, Europe.
In this work, the imaging algorithm called MIDAS (Multi-Instrument Data Analysis Software) has been used. All combinations of constellations have been analysed and compared to the result of the GPS-only solution. The analysis demonstrates the improvement of multi-GNSS tomography in accuracy and resolution over GPS-only for ionospheric electron density imaging.

Satellite Laser Ranging (SLR) is a precise geodetic technique that provides range measurements to artificial satellites equipped with laser retroreflectors. The International Laser Ranging Service (ILRS) unites and coordinates all laser stations and their activities in terms of tracking satellites. Due to the fact that all the Galileo satellites are equipped with the laser retroreflector arrays and at least 8 out of 26 Galileo satellites are considered in the priority list of the ILRS, SLR measurements are performed with cm-accuracy. As a result, the SLR technique can be used for the validation of GNSS-derived products v and for the independent Galileo orbit determination.

SLR serves as an independent validation technique for the GNSS-derived orbits due to the fact that SLR uses optical wavelengths in contrast to GNSS which is based on the microwave observations. Since March 2017, a new Associated Analysis Center (AAC) of the ILRS has been established at Wroclaw University of Environmental and Life Science (WUELS) who runs an online platform GOVUS for the SLR validation of microwave-based orbit products. The web-service GOVUS allows the users to perform fast and advanced online analyses on the stored SLR validation results which are calculated automatically.

Apart from the independent validation tool, SLR solely may serve for the determination of the GNSS satellite orbits. We calculated the boundary conditions for the precise Galileo orbit determination using at least 60 SLR observations provided by 10 homogenously distributed SLR stations within 5 days. Based on solely SLR data we obtained Galileo orbits with the accuracy at the level of 4 cm.

The SLR constitutes a valuable tool for both the accuracy assessment as well as an independent orbit product provider. However, based on the two techniques it is possible to provide the combination of two types of observations whose preliminary results will be in this contribution.

Europe is covered by various networks of GNSS stations maintained by different agencies with different technical and scientific objectives. The geodetic GNSS component of the European Plate Observing System (EPOS) aims to provide services optimized for Solid Earth Research applications through an e-infrastructure for data, metadata, and dedicated products collection and dissemination. We present here the efforts carried out by the members of this group to create a distributed software architecture called GLASS (GNSS Linkage Advance Software System) for disseminating standardized and quality-controlled data, metadata and products (coordinates, velocities and strain rates), scaled for thousands of stations. We describe the data flows from data suppliers and analysis centers to the various EPOS nodes and data & products portals, and its integration into the overall EPOS system and European GNSS community. The quality control steps that are performed on both the GNSS data and products (e.g. validating the station log files, computing quality metrics of RINEX files, comparing solutions from several processing strategies, …) are outlined. Finally, we detail the technologies and software that are used and developed to build this e-infrastructure. EPOS-IP is a project funded by the ESFRI European Union.

Estimation of the linear horizontal gradients in the atmospheric refractivity is today a standard method in GNSS data processing, both for high precision geodesy and for meteorological applications. We compare estimated gradients from GNSS data with observations by a ground-based microwave radiometer (referred to as a water vapour radiometer, WVR) at the Onsala Space Observatory on the west coast of Sweden. We have approximately four years of data (2013–2016) from two GNSS stations and the WVR. The GNSS data are almost continuous, whereas there are some gaps in the WVR data. These are due to hardware failures and rain events. The algorithm for calculation of the water vapour induced path delay becomes inaccurate when there are large liquid water drops present in the observed air mass. Large means here that the sizes of the drops are not much smaller than the shortest wavelength of the observed emission from the atmosphere, which in this case is 1 cm.

The size of the estimated gradients, both from GNSS and the WVR, depends on the spatial and the temporal averaging. This dependence is investigated by carrying out averaging of the original gradient time series with a resolution of 15 min. We will study hourly, daily and monthly averages as well as different elevation cutoff angles for the GPS observations. Because the observatory is located within a few hundred metres from the coastline, oriented mainly in the north-south direction, we will characterize and compare the east and the north components of the estimated gradients. We will also examine the consistency between the gradient results inferred from the WVR and the GNSS observations acquired during different conditions in terms of how much liquid water that is present in the atmosphere. A strict editing of the WVR data, rejecting observations indicating a liquid water content above a specific value, will of course limit the amount of data that can be used to assess the estimated gradient from GNSS. Therefore, we will investigate different editing criteria and study the consequences.

The recent years have seen the accelerated development of Global Navigation Satellite Systems (GNSS) and data-processing techniques, assisted by land-based augmentations aiming to provide a significant improvement of the associated positioning and navigation services. During the years 2005-2010, the GNSS evolution, including the existing GPS and GLONASS systems modernizations, the BeiDou system deployment, the Galileo system preliminary validation (two satellites Galileo In-Orbit Validation Element) and the QZSS development, constitutes an important turning point.
In this context, and following their respective missions, CNES and IGN have agreed in 2012 to collaborate to the establishment, operation and maintenance of a real time GNSS observation infrastructure, including the enhancement for scientific or operational needs related to the GNSS positioning and navigation.
Called REGINA (GNSS Network for IGS and navigation), the project results in the acquisition of multi-GNSS data, in controlled configurations, and the dissemination for the benefit of the scientific community on a long-term approach.
This collaboration between the CNES and the IGN is a continuation of several decades of close relations in various fields of their competence, notably as examples in space geodesy within the DORIS program and in Earth observation within the Spot or Pleiades programs.
By now REGINA is a worldwide network of GNSS stations for IGS and navigation with 35 stations providing a global geographic coverage. It provides Real-time NTRIP streams to IGN casters and CNES caster with 1 Hz data and consolidated data files (15mn, 1h and 1 day). REGINA has a multi constellations capability including GPS/GLONASS, GALILEO, BEIDOU and also SBAS. The Data Management Center for network monitoring and data provision is Located in Toulouse, in CNES premises, with a redundant center at IGN, Paris area. REGINA provides an important amount of GNSS data to scientific community through its contribution to the IGS and contributes to the International Terrestrial Reference Frame with few major sites including GNSS, DORIS, VLBI and Laser technologies. REGINA also contributes to the survey and calibration of GNSS systems and services by providing appropriate data to the CNES navigation experts.
Over the past years, Galileo constellation raised to a number of 26 satellites, 22 are currently operational and full capability is expected for 2021. Value added services will be provided to users through the benefit of the E6 signal such as high-accuracy service (HAS). HAS which will allow to get a positioning error below two decimeters will be based on the free transmission of Precise Point Positioning (PPP) corrections through the Galileo E6 signal data.
To support these Galileo services, CNES and IGN decided to upgrade a large part of REGINA Network since the beginning of 2018 to get E6 reception capability and provide full Galileo data to the User Community through IGS. This paper provides an overview of the REGINA network of stations with a focus on E6 capability.

In the last years, we have been witnessing a very fast development of the Global Navigation Satellite Systems (GNSS). The number of satellites which transmit navigational signals rapidly comes to nearly one hundred. GPS and GLONASS are complemented by newly-established Galileo and BeiDou. This ongoing progress improves the constellation geometry which allows for obtaining a position in a challenging environment. Additionally, a larger number of signals may improve the quality of the products provided by GNSS e.g. tropospheric products. Broadcasted orbits and clock products provided to the users are insufficient to obtain a precise solution. Thus, in order to increase the quality of the obtained results corrections to the products, such as orbits and clocks, are needed. The multi-GNSS Experiment established by the International GNSS Service (IGS-MGEX) provides precise products supporting all navigation systems. Although the products provided by the MGEX are well determined, they are available with a latency, which prevents them from being used in real-time applications.
Real-time applications need to be supported immediately by corrections transmitted to the users e.g. via Internet streams. One of the centers which transmit corrections for quad-system constellation is Centre National d'Études Spatiales (CNES). Products delivered to the users in real-time may improve absolute positioning techniques such as Standard Point Positioning (SPP) or Precise Point Positioning (PPP). However, in order to hold the real-time regime, the products sent via RTCM messages may be affected by outliers. Additionally, due to differences in system configurations and the variety of satellite constructions, the quality of multi-GNSS products is inhomogeneous, which may cause the solution degradation and should be considered at the stage of the observation weighting. There is no comprehensive information about the real-time products quality and their possible changes related to, e.g. modifications of solution strategies. Such information would support users utilizing real-time corrections and might increase the quality of solutions they provide.
Hence, in order to fill the existing gap, we propose to establish a service which would provide continuous, current, and up-to-date information about the real-time clock and orbit corrections for the whole multi-GNSS constellation. The service would provide information about the orbit and clock quality possible to obtain when using RTCM messages. Users will be able to determine both archival as well as the current quality of products described by the Signal in Space Range Error (SISRE) parameter. Users could also determine SISRE for selected GNSS in any time span. Additionally, the graphical illustration will bring supplementary information about changes in the quality of products over time. The products provided in the proposed service may constitute the background for appropriate weighting of multi-GNSS observations increasing the potential of the absolute real-time positioning techniques.

Water vapour is a key variable of the water cycle and plays a special role in many atmospheric processes controlling weather and the climate. Extreme weather events, such as storms, floods and landslides, heat waves and droughts, are one of the main concern of society. The Global Navigation Satellite System (GNSS) is one of the very few tools that can be used as atmospheric water vapour sensor and, simultaneously, provide continuous, unbiased, precise and robust atmosphere condition information. Significant influence on the determination of parameters in the post-processing of satellite observations has undoubtedly the model of phase centers of GNSS antennas.
The aim of this study is to investigate the impact of different GNSS antenna calibrations models on the quality of the tropospheric estimate series for climate applications. We analyse zenith total delays (ZTD) and zenith wet delays (ZWD) obtained from GNSS data processing and afterwards converted integrated water vapour (IWV). One year of GNSS data collected at 19 European Reference Frame (EUREF) Permanent GNSS Network (EPN) stations were processed with NAPEOS software. Zero-differenced Precise Point Positioning (PPP) technique utilizing ESA (European Space Agency) precise satellite orbits and clocks, was used to estimate tropospheric parameters. Several different processing variants were inter-compared. The first solution was obtained by applying the International GNSS Service (IGS) type-mean Phase Center Correction (PCC) models. In the second and third solutions PCC models from , individual field robot calibration and calibration in anechoic chamber respectively were used. All three solutions were processed twice – using GPS only and multi-GNSS (GPS+GLONASS) observations. Moreover, in order to validate and assess the quality of the GNSS solutions, tropospheric parameters obtained from ERA5 reanalysis were compared to GNSS estimates.
In general, the results show that NAPEOS software can provide high quality GNSS tropospheric delay time series. Overall, the mean standard deviation of ZTD differences is higher for differences between variants using observations from different satellite systems than for variants using different antenna calibrations models. However, the impact of applying individual calibrations is not negligible. The results depend strongly on the equipment (receiver and antenna) of the stations. Validation against data from climate reanalysis confirms that all approaches provide high-quality tropospheric delays. Also, there is a high agreement in the IWV distributions between GNSS and ERA5.

In recent years the precision of clocks considerably increased. This makes them very attractive for a number of puposes: (i) improved tests of General Relativity or search for generalized theories of gravity, (ii) geodesy and reference frames, and (iii) space metrology. Regarding tests of General Relativity one can think of (a) improved test of the gravitational redshift, (b) confirmation of the gravitomagnetic clock effect what is a not yet measured effect predicted by General Relativity, (c) improved test of the Shapiro time delay. With clock comparison one may also (d) improve the test of the validity of Universality of the Gravitational Redshift. We will give an overview over all these clock effects in Relativistic Gravity and will outline the proposal to measure the gravitomagnetic clock effect.

The IAG (International Association of Geodesy) Regional Reference Frame subcommission 1.3a for Europe, EUREF (http://www.euref.eu/) is maintaining the EUREF Permanent Network (EPN) covering the European continent (plus North Africa and Middle East). It is a science-driven network of continuously operating GNSS reference stations with contributions from 40 countries. The EPN is supported by station providers, operational centers, data centers, analysis centres (ACs) and the Central Bureau which is responsible for the day-by-day management and the monitoring of the EPN. All contributions to the EPN are voluntary, with more than 100 European (mapping) agencies and research institutes involved. Providing redundancy is one of the key factor for the reliability of EPN data and products. In order to optimize the operational EPN data processing, the principle of distributed processing is used. In this approach, the EPN is divided in subnetworks, separately processed by different ACs following well-defined guidelines. The AC estimate daily and weekly station positions and station zenith tropospheric path delays for a part of the EPN stations. At least three ACs process each EPN station, which is an indispensable condition for providing combined products for site coordinates and troposphere.
As of March 2019, the EPN network contains 336 permanent stations with about 63 % of them collecting and distributing Galileo data. At the EUREF symposium 2018 held in Amsterdam, the EUREF plenary adopted a resolution encouraging the ACs to build up the capabilities for processing Galileo observations and asking the EUREF community, GSA, ESA and the GNSS industry to provide the missing receiver antenna calibrations for Galileo signals. Following this resolution, some ACs started creating GNSS processing solutions including Galileo observations in addition to GPS and GLONASS, in parallel to the operational GPS+GLONASS solutions, and making them available to the Analysis Centres Coordinator and the Troposphere Coordinator, so that the impact of Galileo observations on the combination products could be analyzed. In comparison with the operational combined solutions, mean position differences (over 33 weeks) for the majority of stations did not exceed 1 mm in the horizontal components, and 3 mm in the vertical component. For troposphere, the differences in the total zenith delays were below 1 mm. It was therefore decided to stop the test phase and to start including Galileo observations in the EPN operational products. Since all the ACs providing the solutions during the test phase agreed to switch to Galileo solutions operationally, it was decided to officially start 3G (including Galileo observations) at the same time, i.e., since GPS week 2044.
In this presentation we will describe the efforts undertaken within the EPN to collect and distribute Galileo observations at the reference stations as well as the impact of Galileo observations have on the EPN products, in particular positions and troposphere.

Acknowledgment
We acknowledge all the EPN ACs for providing operational and 3G solutions as well as the GNSS site owners for the collection and distribution of Galileo data in addition to GPS and GLONASS.

The network RTK positioning is considered as a technique which provides reliable, accurate and fast position solution. The performance of the method depends to a high extent on the accuracy and availability of the ionospheric corrections derived by the reference network. This is especially valid in the long-range scenario with baselines over 100 km and during high ionosphere activity or occurrence of different scale ionospheric disturbances. Hence in such scenario the network ionospheric correction may not always meet the requirements to support integer ambiguity resolution and, as a consequence, precise GNSS positioning. Even the integration of multi-constellation observables may not overcome the negative impact of the strong ionospheric disturbances.
This contribution presents the feasibility study of the innovative algorithm supporting multi-constellation network RTK under extremely varying ionospheric conditions. The developed algorithm is based on the rate of TEC equation and aims at elimination of the temporal variations of the ionospheric delay. The experimental verification was conducted on the basis of data collected by permanent GNSS stations constituting wide-area network at high latitudes during ionospheric storm on 25-26.08.2018. The results confirmed a clear deterioration of RTK performance in such scenario, which was mainly caused by drop of the ionospheric correction accuracy.
On the other hand we observed noticeable benefits from the application of the innovative algorithm. The results proved high applicability of the algorithm, specifically demonstrating a distinctive improvement in the ambiguity resolution domain, therefore proving the advantage over standard network RTK solution. Hence with the support from the developed algorithm it is feasible to provide fast and accurate long-range RTK solution under strong ionospheric disturbances.

Accurate and reliable state estimation is an issue for autonomous robots. Heading and tilt are critically important state variables which are further used in mapping, localization and control algorithms in most of the autonomous robots pipeline. In drones, heading and tilt play pivotal roles to determine flight direction. Accurate heading and tilt can provide precise velocity in robot frame from GNSS doppler velocity in global frame. Furthermore, it is also used for improving efficiency and user comfort in cars by controlling for roll and pitch.

Heading and tilt estimation is challenging because dual GNSS provides positioning information which have high variances and thus result in poor heading with shorter baseline. Furthermore, the frequency of GNSS is low which poses a challenge for attitude estimation in highly dynamics robots such as drones. Although, IMUs can provide precise angular velocities at high frequencies but they are corrupted with time varying bias and drift. Magnetometers are often used for attitude estimation, however, this can lead to crashes when robots encounter heavy electromagnetic fields. Moreover, outliers and sensor failures due to environmental conditions pose other challenges when using these sensors.

This paper addresses the issue of heading and tilt estimation using an RTK based dual GPS receiver combined with IMUs. Heading and tilt estimator is composed of two kalman filters used in a cascaded fashion. First, the linear kalman filter (LKF) fuses 2 IMUs. The goal of this is to reduce drift and bias using a drift model and an online bias calculator, respectively. The second kalman filter is a state constraint extended kalman filter (EKF) used to fuse dual GNSS receiver and IMU data to obtain a baseline vector between the receivers. RTK based GNSS receivers from Fixposition are used, which are known to provide 1 cm accurate location. The GNSS positions are converted to ENU coordinates. ENU coordinates are subsequently propagated in EKF, instead of heading and tilt angles, due to its continuity and homogeneous nature with respect to both the sensors. Thus, these ENU coordinates serve as states of EKF and are propagated using IMU angular rates. A prior constraint is imposed on the state vector which is marked to remove drift of the gyroscope. A chi square based outlier detection has been implemented in the EKF, which rejects sensor data if it is outside 3σ bound. Heading and tilt are finally calculated from the state vector of the EKF. The estimation can be further improved by learning residual of the state constraint. This residual can then be used to predict and remove bias from the IMUs.

The described setup was built and tested for drones due to their small size and having high dynamics. Heading accuracy can be improved for larger robots as their baseline can be widened. This setup provides heading accuracy of 0.4° with a baseline of only 22cm. RTK based positions are used in this approach to estimate the baseline vector, which can be further improved by estimating it from the dual GPS receiver without position estimation.

It is well established that GNSS (Global Navigation Satellite System) contribution is fundamental for seismology and ionospheric seismology. The purpose of this research is to leverage simultaneously the same GNSS data stream to analyse both the earthquakes’ ground motion and the total electron content (TEC) disturbances in real-time. This aim is obtained through two different algorithms, which both use the variometric approach, leading to the definition of the so-called total variometric approach (TVA). In particular, the VADASE (Variometric Approach for Displacement Analysis Stand-alone Engine) algorithm [1], is able to characterize the velocities and displacements of the ground motion in real-time, while the VARION (Variometric Approach for Real-Time Ionosphere Observation) algorithm [2] is able to detect the slant TEC (sTEC), in essence the TEC on the satellite-receiver line of sight without any geometrical correction, variation in real-time. This methodology was applied in a real-time scenario to the 8.3 magnitude earthquake that occurred in Chile on September 16, 2015. The connection between the ground motion and the earthquake induced ionospheric perturbation observed 8 min after the seismic rupture [3] was extensively investigated. The results clearly show the effectiveness of the proposed real-time TVA based on the VARION and VADASE algorithms coupled together. TVA can run in parallel but independently, using the same GNSS data stream as input. Therefore, TVA is ready to be implemented on still existing high-rate GNSS.
Hence, the ultimate goal of this research is to employ this real-time information for the enhancement of already existing tsunami warning systems.

References

[1] Colosimo, G., Crespi, M., and Mazzoni, A. (2011). Real‐time GPS seismology with a stand‐alone receiver: A preliminary feasibility demonstration. Journal of Geophysical Research: Solid Earth, 116(B11), doi: 10.1029/2010JB007941
[2] Savastano, G., Komjathy, A., Verkhoglyadova, O., Mazzoni, A., Crespi, M., Wei, Y., and Mannucci, A. J. (2017). Real-time detection of tsunami ionospheric disturbances with a stand-alone GNSS receiver: A preliminary feasibility demonstration. Scientific reports, 7, doi: 10.1038/srep46607
[3] Occhipinti, G., L. Rolland, P. Lognonné, S. Watada, From Sumatra 2004 to Tohoku-Oki 2011: The systematic GPS detection of the ionospheric signature induced by tsunamigenic earthquakes , J. Geophys. Res., 118, doi:10.1002/jgra.50322. 2013

POSITRINO is an ESA NAVISP-I project kicked-off in 1Q 2019 devoted to study the possibility of using neutrinos for Position, Navigation and Time applications. The consortium is led by GMV-UK with University of Liverpool as subcontractor. Given the innovation required to deliver the project, an external advisory board formed by European and non-European delegates with credentials of the highest caliber is being set up.
Neutrinos are among the most abundant particles in the universe, nearly massless, travel at speeds near the speed of light and are electrically neutral. Neutrinos can be generated through man-made sources like nuclear reactors and particle accelerators or by natural sources like the sun and other celestial bodies.
Neutrinos only interact via the weak force and gravity. Since gravitational interaction is extremely weak and the weak force has a very short range, neutrinos can travel long distances unimpeded through matter, reaching places inaccessible to GNSS signals.
Different activities have been undertaken in the past by NASA and Universities with the goal of using neutrinos for communication or PNT applications.
The main objective of this project is to provide an early design of a Neutrino PNT system and analyse its feasibility for certain applications for which there are no other PNT technologies available, or if there are, they are too costly or provide poor performances. A preliminary list with potential applications investigated in the project covers submarine navigation and communication, subsurface positioning, space assets positioning or tracking, or back-up systems for severe GNSS disruptions.
Neutrino PNT concept would be based on using artificial and/or natural neutrino sources as the signal and the user equipment would include a neutrino detector and a processing SW. PNT algorithms analysed in the project could be based on different techniques, as determination of the angle of arrival of the signal neutrinos or an equivalent concept to GNSS ranging based on time of arrival.
Based on a state-of-the-art review, the project identifies requirements, gaps, solutions, benefits and limitations of the Neutrino PNT concept in order to identify a suitable high-level design based on technology trade-offs. Although a PNT system based on neutrino particles may be possible, important challenges like scale to operational size, neutrino detection and the discrimination of the signal vs background should not be ignored. Neutrinos are difficult to detect, then, neutrino detectors are big and costly. Therefore, studying concepts for miniaturization of neutrino detectors which at the same time provides acceptable detection rates is an important aspect in the project. Neutrino sources and the isotropy or collimation of the neutrino flux, which determines the coverage area of the system, are also studied. Coding and decoding schemes, neutrino beam characterization and the detection rate, acquisition and tracking are also areas of interest for POSITRINO project.
Finally, the different concepts analysed are tested using available neutrino and PNT software and data. After a feasibility analysis of the recommended option, the second phase of the project is devoted to the design a Proof-Of-Concept with the potential to be implemented in future activities.

The troposphere total delay derived from GNSS observations can be divided into a hydrostatic part caused by the dry gases in the atmosphere and a wet part caused by the refractivity due to water vapor. Due to the consistent data analysis in terms of methods and models and due to growing length of the time series, ground-based GNSS is becoming an independent and more and more important data source in climate monitoring. This contribution tries to carefully analyze and assess the quality of the long GNSS time series for their potential use in climatology.
In this contribution, 11 years of global GNSS data was reprocessed from 2002 to 2012 with three kinds of solutions, namely GPS-only, GLONASS-only and combined GPS/GLONASS solutions. In the parameter estimation, 6-hourly ECMWF-based hydrostatic delays mapped with the VMF1 have been used as a priori troposphere delays without including a priori gradients. Two-hourly piece-wise linear wet troposphere zenith delays, mapped with the wet VMF1 mapping function, and 24-hourly troposphere gradients have been estimated for each station. Much care has been taken to model all the station motion effect such as solid Earth tides, pole tides, ocean and atmospheric pressure loading in order to avoid a propagation of these effects into the troposphere zenith wet delay estimates (ZWD).
Based on these reprocessed time series, we studies, firstly, the long-term formal errors of the ZWD time series of each solution. The formal errors are not only affected by the number of GNSS observations contributing, but also by the season (amount of water vapor) and the performance of the equipment. Unfortunately, there are hundreds of equipment change in the GNSSS stations during these 11 years, degrading the accuracy of estimating ZWD drifts that most interesting for climate change.
Secondly, we studied the differences in the ZWD estimates between the three solution types in order to check, whether there are any system-specific biases in the ZWD estimation. In October 2011, the full orbital constellation of 24 GLONASS satellites was re-achieved. We also carefully look at the effect of different antenna types on the ZWD estimates by grouping stations with the same antenna type.
Thirdly, we studied the periodic terms in the long-term ZWD time series. It turns out that there are several long-period terms and several sub-daily short-period terms. Thereby, the stations near the ocean show significant correlation with M2. This suggests that the ocean loading models are still containing biases, especially close to the coast. The amplitude of each term ranges from 0.4 mm to 70 mm.
In summary we can see that there is a small systematic bias in the ZWDs between GPS and GLONASS that is getting more and more important, as the GLONASS constellations is replenished. In addition, there are several long (and short periodic) variations in ZWD that can affect the long-term trends. Considering the correlation between ZWD and temperature is helpful, to get a better insight into the use of GNSS ZWDs for climate monitoring and forecasting in the future.

Nowadays, Global Navigation Satellite System (GNSS) is one of the most trustworthy and popular positioning systems. For now, most GNSS users use the non-civilian American (GPS) or Russian GLONASS signals. But, what would happen if these signals are suddenly switched off one day? Therefore, Europe is unique in that it is the only region to develop a GNSS system for civilian applications. Galileo is created by the European Union (EU) through the European GNSS Agency (GSA) and its full operation is foreseen for 2020. With the addition of Galileo to the GNSS constellation, we not only avoid GPS and GLONASS signal dependencies, but also provide improved positioning for the end GNSS user. For now, more and more services become dependent on the availability of an accurate GNSS signal such as: monitoring, tracking, surveying, sport watches etc. That’s why, the principle role of the multi-constellation GNSS positioning is to eliminate the faults signals to ensure accurate GNSS positioning.
There are many algorithms and methods to improve the positioning accuracy. For example, the WLSE (weighted least-squares estimation) is one of the most commonly used. In this algorithm, satellite elevation angle and SNR (signal to noise ratio) are used to compute the observation weights. However, they are not always useful since they are impacted by the multipath and radio interferences especially in urban canyons.
This paper presents a robust MM class estimator for the GNSS positioning using data from the Galileo in combination with GPS data. Robust estimation algorithms perform statistical analysis of test data to detect and exclude the outlier data measurements for more accurate estimation. A robust estimation algorithm is defined based on three factors: efficiency, stability and breakdown point. Efficiency is the performance of an estimator. A robust estimation process must be stable to avoid impair the performance. The measure of the maximal fraction of outlier observations in any data for a robust estimator, without spoiling the final estimate, is defined as the breakdown point. The role of this method is to harmonize the above three features.
To demonstrate the algorithm, this paper uses the Galileo data in RINEX 3.02 and GPS data from ABMF station in RINEX format 2.11. This reference station is located in Guadeloup. RINEX data and broadcast ephemeris used for calculation were downloaded from the website https://cddis.nasa.gov for day 01 January 2019. For the performance evaluation of the proposed method, root mean square error (RMSE) is used. With Galileo data only, the RMS (Root Mean Square) position errors are E_RMS = 1.26 (m), N_RMS = 1.03 (m) and U_RMS = 2.6 (m). Using the robust estimation, they are reduced to: E_RMS = 0.75 (m), N_RMS = 0.69 (m) and U_RMS = 1.84 (m).
In future works, we will perform fusion of GNSS measurements with other sensors such as IMU (Inertial Measurement Unit) and vision sensors to improve the positioning accuracy.
The authors would like to note that this abstract falls under the umbrella of topics N03 and N05

The National Aeronautics and Space Administration (NASA), Defense Advanced Research Projects Agency (DARPA), United States Air Force (USAF) and Federal Aviation Administration (FAA) have successfully partnered to fund, develop, test, and transfer the NASA/DARPA Autonomous Flight Termination Unit (AFTU) technology to U.S. commercial space companies. An Autonomous Flight Termination System (AFTS) is an independent, self-contained system mounted onboard a launch vehicle. AFTS autonomously makes flight termination/vehicle destruct decisions for public safety/range safety using configurable software-based rules implemented on redundant flight processors using data from redundant navigation sensors. The ability to perform this function on the launch vehicle results in tremendous cost savings by eliminating the need for ground personnel, transmitters, telemetry receivers, and radars historically used for this purpose. It also provides global coverage because launch vehicles using AFTS no longer need to be launched from a dedicated range. AFTS can also support multiple vehicles simultaneously, such as flyback boosters. The Autonomous Flight Termination Unit (AFTU) is the AFTS subsystem that interfaces with external navigation sources, such as GPS and/or INS/IMU, and generates a termination recommendation if necessary based on the violation of mission rules. The AFTU also interfaces with ordnance/thrust termination subsystems, telemetry, and power.
The four partners in the AFTU transfer story each had a unique role in its success. DARPA, through its Airborne Launch Assist Space Access (ALASA) program, provided funding for AFTU research, design, and development, as well as providing launch opportunities aboard various launch vehicles for AFTU hardware and software testing. NASA Kennedy Space Center (KSC) performed the design, development, and test of the AFTU hardware and software. The USAF 30th and 45 Space Wings, along with the FAA, contributed to the AFTU effort by helping to oversee and approve NASA AFTU requirements, design, test, and operation of AFTU software and hardware for government and commercial space operational use. The CASS, originally developed by NASA, then modified by the USAF 30th SW for operational use, is mission critical for any launch vehicle equipped with an AFTU because it contains the algorithms used by the AFTU to make flight termination/vehicle destruct decisions. This cooperative joint effort was key to the development of the AFTU that meets all safety critical requirements for operational use.
The result of this four-way partnership is a generic engineering version of the AFTU hardware and wrapper software along with CASS software that can be used by commercial space companies as a baseline for developing their own versions of the system for their launch vehicles. This will help significantly shorten each company's development timeline and cost. The KSC Technology Transfer Office has to date completed 40 transfers of the AFTU technology to commercial space companies.

GNSS Radio Occultation (GNSS-RO) observations have provided in the last 20 year a huge amount of data suitable to perform Global Change studies and Operational Meteorology on global range. The main drawback when the technique is applied, regard the availability of only two equations ( Smith & Weintraub refractivity at microwave wavelength and and hydrostatic equilibrium law combined with state equation of ideal gas) but three unknown: Pressure, Temperature and Humidity profiles. Usually the rank deficiency is sloved merging observations with model in simple mode or applying 1DVAR technique. The authors apply an innovative “simple “method (BPV) which avoids the use of external information. Our BPV approach can be classified among the “Simple" methods. BPV works with dry atmospheric models which depend on latitude, DoY and height (CIRS86aQ) or Surface Pressure and Temperarure (Hopfield) . The dry refractivity profile is selected estimating the involved parameters in a non linear least square fashion achieved by fitting GNSS-RO observed bending angles (BA) through the stratosphere where the humidity is negligible. Then we extrapolate the hydrostatic refractivity or BA down to Earth surface. Thus we achieve humidity subtracting from real observations the dry contribution. BPV approach as well as all the other “Simple" methods, has as drawback the unphysical occurrence of “negative” values of humidity. So we have developed a couple of approach in order to overcome negative humidity problems. The idea is to perform least square non linear fitting with positive residuals constraint. From mathematical point of view we have implemented this solution applying two different approach. The first one implement a second step of minimization introducing a weighting scheme where negative values of residuals are made negligible. In the second one the non –linear fitting was achieved by modifying the usual least square functional with the addition of fast increasing exponential terms with respect to positive residuals. In both approach we have applied the Levenberg-Marquardt non linear fit approach. After a proper tuning of the approaches, we will present the results of comparison and validation of both the approaches.

Space-based radio system in L-band, like the Global Navigation Satellite Systems (GNSSs), are severely affected by the ionospheric errors, which shall significantly degrade the performance of GNSS navigation and positioning applications if not properly corrected. We focus on two ionospheric correction models for real-time global ionospheric error mitigation. One is the broadcast ionospheric model of Galileo system, NeQuick Galileo (NeQuickG), used for single-frequency ionospheric correction of Galileo users. The other is the real-time global ionospheric maps (RT-GIMs) generated by the real-time GNSS data streams of the International GNSS Services (IGS) real-time services (RTS). Aside from the assessment of NeQuickG coefficients routinely transmitted by Galileo satellite vehicles, a method for the re-estimation of NeQuickG coefficients using ground-based GNSS observations is presented. The quality of the re-estimated NeQuickG coefficients is evaluated during the solar cycle 24 by comparison with respect to (w.r.t.) the vertical electron content (VTEC) data provided by the IGS GIM and Jason altimetry, which illustrates the overall performance of NeQuickG model during different levels of solar activity. For RT-GIM generation, the method for real-time global VTEC modeling using the IGS RTS is first presented, followed by the validation w.r.t. GNSS differential slant TECs (dSTEC) and Jason VTECs cover the continental and oceanic regions, respectively, during a recent 2-year period (2017-2018). With the consideration of the real-time capability of NeQuickG and RT-GIM for pronounced ionospheric error mitigation, the improved standard (using NeQuickG) and precise (using RT-GIM) GNSS applications can be foreseen.

GNSS code pseudorange measurements exhibit group delay variations at the transmitting and the receiving antennas. They are of importance for all those applications which depend on precise and unbiased code measurements, as e.g., PPP ambiguity fixing, code based positioning, time transfer, and ionospheric monitoring.

We determined GDV from reference station observations made available by IGS, EPN, NGS, and other services. As a result, we obtained combined GDV of transmitting and receiving antennas. No complete separation of the GDV contributions of the satellite antennas from those of the receiving antennas is feasible with these observation data sets. Nevertheless, the use of common receiving antenna types with various satellites or the use of common satellites with various receiving antennas, enables the determination of relative GDV corrections. Adding up such corrections of satellite and receiving antennas produces an absolute GDV correction which mitigates the adverse effects on pseudorange measurements.

In this presentation we compare GDV from GPS, GLONASS and Galileo satellites. We identify groups of satellites with similar GDV patterns and also outliers. Furthermore, we show geodetic receiving antennas with significant elevation dependent GDV and even some with a strong azimuth-elevation dependency.

The approach to the terrestrial reference frame (TRF) realization in the processing of the global GNSS observations affects the quality of the global geodetic products. The reference frame in the GNSS processing is typically realized by applying minimum constraint conditions on the network based on the set of the most stable datum stations. Based on minimum constraint conditions we can constrain three translations (NNT), three rotations (NNR) and one scale parameter (NNS) between two considered frames. Actually, a No-Net-Rotation condition is mandatory when the orbits are estimated simultaneously with station coordinates and Earth rotation parameters. In a global solution, the No-Net-Translation condition is related to the estimation of geocenter parameters and needs to be handled accordingly in GNSS solutions.

The purpose of this study is to analyze differences in GNSS products, such as in station coordinates, Earth rotation parameters, geocenter coordinates (GCC), and satellite orbits delivered from the double-difference multi-GNSS (GPS, GLONASS, and Galileo) processing using different approaches to the TRF realization and different approaches to handling of the geocenter motion. Three solutions are analyzed with: (1) NNR-only, a pure minimum constraint solution; (2) NNR+NNT+GCC estimation derived from expanding the normal equations in terms of estimating the geocenter and to overcome the translation rank-deficiency; (3) NNR+NNT, an over-constrained solution, directly dependent on the minimum network constraints.

The results show that we cannot realize a reliable CoM frame in global GNSS analyses with the accuracy better than 4 mm. Therefore, using both NNR and NNT constraints on the network is beneficial for the repeatability of station coordinates. When the NNT condition is imposed on the network, the station repeatability can be improved by 71%, 50%, and 29% for the North, East and Up components, respectively. This effect is fully explainable by the impact of the erroneous “apparent GCC” which contains not only the signal of the geocenter motion but also orbit errors, and a limited sensitivity of GNSS observations to the CoM. When NNR+NNT are used and the GCC are not estimated, the impact of “apparent GCC” as seen by GNSS is spread over other estimated parameters, such as station coordinates, ERPs, and orbits.

Transionospheric radio signals, especially those of Global Navigation Satellite Systems (GNSS), can be used to study ionospheric disturbances induced by natural and impulsive phenomena such as earthquakes, tsunamis, and volcanic eruptions. Shallow and large earthquakes (Mw > 6.5) trigger Coseismic Ionospheric Disturbances (CID) regularly observed in GPS-derived Total Electron Content measurements. The disturbances are generated at ground level: the sudden vertical motion of the Earth’s surface pushes the atmosphere above, producing an acoustic pulse (thus the coseismic uplift is considered as the “acoustic source”). This pulse propagates upward, shaking the upper atmosphere and the ionosphere. The local change in the electron density induces a change in the propagation time of radio signals that can be measured using GNSS. We can directly and accurately derive the change in the integrated electron density (namely Total Electron Content: TEC) using the geometry-free combination of multi-frequency GNSS measurements. Furthermore, GNSS satellites offer the capability to sound the ionosphere in all directions, including far from the receiver with satellites are tracked close to the horizon (elevation angle: 10-20°). This method allows monitoring underwater - hence potentially tsunamigenic - earthquakes occurring in subduction zones, often far from the ground-based conventional monitoring networks.
The overall challenge is thus to use the ionospheric signature computed from GNSS-derived TEC data in order to rapidly characterize the localization, amplitude and size of either the initial crustal uplift inland or the initial tsunami wave over the ocean. This study specifically focuses on the acoustic source localization problem with the example of the megathrust earthquake that occurred near the city of Pedernales in Ecuador on April 16, 2016 as a case study. Through simulations, we show how additional Galileo satellites will benefit to the acoustic/tsunami source localization problem. This method consists in three main steps. (1) We first model the acoustic wave triggered from a point source on the Earth’s surface, its propagation and its interaction with the atmosphere and the ionosphere. (2) We then reconstruct the coseismic TEC perturbation signature for any given GNSS satellite-receiver pair by integrating the computed electron density perturbation along the corresponding line-of-sight (LOS). (3) A geographical grid search method is finally used to constrain the best fitting acoustic source location. After discussing the performance and limitations of the method on real data, we further highlight how the observation geometry from additional GNSS constellations improve the localization. We finally discuss the novel perspectives offered by the multi-GNSS frequencies (L5, E5) for co-seismic ionospheric signatures monitoring.