This study presents a comparison of tropospheric parameters, namely zenith tropospheric delay and total refractivity calculated using meteorological measurements from a Meteodrone and Global Navigation Satellite Systems (GNSS) stations. A Meteodrone is a unique Unmanned Aerial Vehicle (UAV) originally designed for automatic measurements of meteorological parameters in vertical profiles (up to 3 km above ground) for the assimilation into numerical weather prediction models. One profile measured with both ascending and descending drone takes approximately 20 min, and there are multiple flights possible during one night. The measurements for this campaign have been conducted in March 2019, in Marbach, Switzerland. We have collected pressure, temperature and humidity profiles from nine flights. From the measured meteorological parameters, we have calculated the refractivity and zenith tropospheric delays (ZTDs). The parameters are compared with models calculated from 32 neighboring GNSS stations interpolated using the in-house developed least-squares collocation software COMEDIE (COllocation of MEteorological Data for Interpretation and Estimation of tropospheric path delays). The comparisons between the Meteodrones and the GNSS-derived models show a good agreement with an average absolute bias of 2.4 mm with 1.5 mm standard deviation for ZTD and 2.7 ppm with 1.7 ppm standard deviation for the comparison of the refractivity. The bias is a result of local changes of meteorological conditions captured by the drone, but not by the interpolation model. (c) 2020 COSPAR. Published by Elsevier Ltd. All rights reserved.

The GPS refractometry method is presented to derive snow water equivalent (SWE) by using refracted GPS L1 signals from a low-cost antenna buried underneath the snowpack. The GPS monitoring system is installed at 2536 m a.s.l. in the Swiss Alps. GPS refractometry is able to correct the influence of the snowpack above the buried antenna. The systematic and stochastic snow induced effects in the GPS residuals are significantly reduced by estimating the SWE above the antenna. The refined method is able to estimate the SWE hourly over a full season and results are highly correlated to the reference sensors data with a median relative bias of less than 10 %.

This paper deals with the detection of small movements of a global navigation satellite system (GNSS) station by means of high-precision estimates of the instantaneous station velocity. The aim is to detect hazardous displacements in real time in order to quickly provide movement information to facilitate a GNSS monitoring system. The station velocities are deduced from time derivatives of GNSS carrier phase measurements. On the basis of epochwise estimates of station velocity, potential movements can be detected by using a statistical hypothesis test. The results from an experimental data set show that the obtainable accuracies of the estimated velocity components can reach a level of a few tenths of a mm/s (1 sigma) and also that it is possible to detect movements on the sub-mm/s level with a high statistical significance. In order to enhance the reliability of the movement detection and to support decision making, two decision criteria extending over several epochs are proposed. The algorithm works in a standalone mode, which means that no data from a reference station or any other external link is needed.

Technological advances in frequency-modulated continuous-wave (FMCW) synthetic aperture radar (SAR) and the associated miniaturization and energy efficiency make it increasingly possible to transfer SAR systems from traditional airborne platforms to small UAVs. An important factor to successfully achieve high-quality imaging from SAR systems mounted on small drones is the precise knowledge of the platform's navigation data in best case by avoiding the use of an expensive and heavy inertial measurement unit (IMU). In this paper, we test different concepts and discuss the impact on SAR image quality using FHR's FMCW MIRANDA35 sensor. To compare several methods simultaneously on one platform and to have an IMU as reference, first preparatory steps were carried out on an airborne platform. Specifically, we present and evaluate solutions based on SAR autofocus, moving baseline differential GPS and optical structure-from-motion-based localization. SAR autofocus shows the best performance in our preliminary investigations.

Global navigation satellite system (GNSS) antennas buried underneath a snowpack have a high potential for in situ snow water equivalent (SWE) estimation. Automated and continuous SWE quantification independent of weather conditions could enhance snow hydrological monitoring and modeling. Accurate and reliable in situ data are needed for the calibration and validation of remote sensing data and snowpack modeling. A relative bias of less than 5 is achieved using sub-snow global positioning system (GPS) antennas (GPS refractometry) during a three full seasons time period in the Swiss Alps. A systematic overview regarding the temporal reliability of the sub-snow GPS derived results is, however, missing for this emerging technique. Moreover, GPS processing impacts the results significantly. Different GPS processing parameters are therefore selected and their influence on the SWE estimation is investigated. The impact of elevation-dependent weighting, the elevation cutoff angles, and the time intervals for SWE estimation are systematically assessed. The best results are achieved using all observations with an elevation-dependent weighting scheme. Moreover, the SWE estimation performance is equally accurate for hourly SWE estimation as for lower temporal resolutions up to daily estimates. The impact of snow on the coordinate solution is furthermore evaluated. While the east and north components are not systematically influenced by the overlying snowpack, the vertical component exhibits a significant variation and strongly depends on the SWE. The biased vertical component therefore provides an additional possibility to estimate SWE.

Abstract. Global Navigation Satellite Systems (GNSS) contribute to various Earth observation applications. The present study investigates the potential and limitations of the Global Positioning System (GPS) to estimate in situ water equivalents of the snow cover (snow water equivalent, SWE) by using buried GPS antennas. GPS-derived SWE is estimated over three seasons (2015/16–2017/18) at a high Alpine test site in Switzerland. Results are validated against state-of-the-art reference sensors: snow scale, snow pillow, and manual observations. SWE is estimated with a high correspondence to the reference sensors for all three seasons. Results agree with a median relative bias below 10 % and are highly correlated to the mean of the three reference sensors. The sensitivity of the SWE quantification is assessed for different GPS ambiguity resolution techniques, as the results strongly depend on the GPS processing.

GNSS antennas suffer from errors, dependent on the direction of the incoming GNSS signal. These errors can be calibrated. We present an absolute field calibration method based on a 6-axis industrial robot. The antenna to be calibrated is set-up on the robot at one end of a short baseline. The robot brings the antenna into 1440 different orientations without changing its coordinates, every orientation lasting for 1 second. The data is analyzed in a triple-difference approach. The estimated GPS L1 phase center corrections show a repeatability better than a millimeter (0.6 mm RMS). We belief that this new method is of interest to the scientific community, as only a few independent field calibration systems exits.

Relative antenna field calibrations were carried out for two attitude determination setups with antennas located within a wavelength of each other. In one case, four Amotech ceramic patch antennas of 18 x 18 mm2 size, in the other case three Trimble Bullet III antennas were used. The results are significant phase center offsets and phase center variation maps. The obtained phase patterns are highly heterogeneous and asymmetrical. These patterns were applied to a simulation of attitude determination onboard a spacecraft in low Earth orbit. Synthetic data was generated with the Bernese GNSS Software V5.2. The analysis revealed the importance of the proper correction of phase center variations. The impact on ambiguity resolution was studied as well. Finally, a field data validation was carried out. The root mean square error of the estimated attitude for a platform with three antennas located within 15 cm of each other, could be reduced from over 6 degrees to 4.5 degrees. A step towards more precise attitude determination on very short baselines was done, but additional efforts are required. Especially the temporal stability of the phase patterns of low-cost antennas remains questionable.

A focus of the Institute for Geodesy and Photogrammetry (IGP) lies on the GNSS data processing for the monitoring of slope movements in high Alpine regions in the Swiss Alps. Thawning of permafrost areas (e.g. rock glaciers) can cause threats for humans and infrastructure. In order to bridge the gap from monitoring in post-processing to early warning in realtime, the IGP is developing and testing algorithms for the instant detection of hazardous slope movements by means of estimates of the instantaneous station velocity based on GNSS Doppler phase observations. This paper focuses on the derivation of a Minimum Detectable Velocity (MDV) for this method. Experimental tests reveal that depending on the sampling interval velocities down to the mm/s-level can be detected. Simulations of the MDV based on static GNSS measurements reveal that it can even be possible to detect movements at the sub-mm/s level. Advantages of this method are the ‘standalone’ solution and the real-time provision of movement information. It thus will strongly contribute to a landslide early warning system.

Observations from a submerged GNSS antenna underneath a snowpack need to be analyzed to investigate its potential for snowpack characterization. The magnitude of the main interaction processes involved in the GPS L1 signal propagation through different layers of snow, ice, or freshwater is examined theoretically in the present paper. For this purpose, the GPS signal penetration depth, attenuation, reflection, refraction as well as the excess path length are theoretically investigated. Liquid water exerts the largest influence on GPS signal propagation through a snowpack. An experiment is thus set up with a submerged geodetic GPS antenna to investigate the influence of liquid water on the GPS observations. The experimental results correspond well with theory and show that the GPS signal penetrates the liquid water up to three centimeters. The error in the height component due to the signal propagation delay in water can be corrected with a newly derived model. The water level above the submerged antenna could also be estimated.

The Empirical CODE Orbit Model (ECOM) of the Center for Orbit Determination in Europe (CODE), which was developed in the early 1990s, is widely used in the International GNSS Service (IGS) community. For a rather long time, spurious spectral lines are known to exist in geophysical parameters, in particular in the Earth Rotation Parameters (ERPs) and in the estimated geocenter coordinates, which could recently be attributed to the ECOM. These effects grew creepingly with the increasing influence of the GLONASS system in recent years in the CODE analysis, which is based on a rigorous combination of GPS and GLONASS since May 2003. In a first step we show that the problems associated with the ECOM are to the largest extent caused by the GLONASS, which was reaching full deployment by the end of 2011. GPS-only, GLONASS-only, and combined GPS/GLONASS solutions using the observations in the years 2009–2011 of a global network of 92 combined GPS/GLONASS receivers were analyzed for this purpose. In a second step we review direct solar radiation pressure (SRP) models for GNSS satellites. We demonstrate that only even-order short-period harmonic perturbations acting along the direction Sun-satellite occur for GPS and GLONASS satellites, and only odd-order perturbations acting along the direction perpendicular to both, the vector Sun-satellite and the spacecraft’s solar panel axis. Based on this insight we assess in the third step the performance of four candidate orbit models for the future ECOM. The geocenter coordinates, the ERP differences w. r. t. the IERS 08 C04 series of ERPs, the misclosures for the midnight epochs of the daily orbital arcs, and scale parameters of Helmert transformations for station coordinates serve as quality criteria. The old and updated ECOM are validated in addition with satellite laser ranging (SLR) observations and by comparing the orbits to those of the IGS and other analysis centers. Based on all tests, we present a new extended ECOM which substantially reduces the spurious signals in the geocenter coordinate \(z\) (by about a factor of 2–6), reduces the orbit misclosures at the day boundaries by about 10 %, slightly improves the consistency of the estimated ERPs with those of the IERS 08 C04 Earth rotation series, and substantially reduces the systematics in the SLR validation of the GNSS orbits.

Homogeneously reprocessed combined GPS/GLONASS 1- and 3-day solutions from 1994 to 2013, generated by the Center for Orbit Determination in Europe (CODE) in the frame of the second reprocessing campaign REPRO-2 of the International GNSS Service, as well as GPS- and GLONASS-only 1- and 3-day solutions for the years 2009 to 2011 are analyzed to assess the impact of the arc length on the estimated Earth Orientation Parameters (EOP, namely polar motion and length of day), on the geocenter, and on the orbits. The conventional CODE 3-day solutions assume continuity of orbits, polar motion components, and of other parameters at the day boundaries. An experimental 3-day solution, which assumes continuity of the orbits, but independence from day to day for all other parameters, as well as a non-overlapping 3-day solution, is included into our analysis. The time series of EOPs, geocenter coordinates, and orbit misclosures, are analyzed. The long-arc solutions were found to be superior to the 1-day solutions: the RMS values of EOP and geocenter series are typically reduced between 10 and 40 %, except for the polar motion rates, where RMS reductions by factors of 2–3 with respect to the 1-day solutions are achieved for the overlapping and the non-overlapping 3-day solutions. In the low-frequency part of the spectrum, the reduction is even more important. The better performance of the orbits of 3-day solutions with respect to 1-day solutions is also confirmed by the validation with satellite laser ranging.