The access to Android-based Global Navigation Satellite Systems (GNSS) raw measurements has become a strong motivation to investigate the feasibility of smartphone-based positioning. Since the beginning of this research, the smartphone GNSS antenna has been recognized as one of the main limitations. Besides multipath (MP), the radiation pattern of the antenna is the main site-dependent error source of GNSS observations. An absolute antenna calibration has been performed for the dual-frequency Huawei Mate20X. Antenna phase center offset (PCO) and variations (PCV) have been estimated to correct for antenna impact on the L1 and L5 phase observations. Accordingly, we show the relevance of considering the individual PCO and PCV for the two frequencies. The PCV patterns indicate absolute values up to 2 cm and 4 cm for L1 and L5, respectively. The impact of antenna corrections has been assessed in different multipath environments using a high-accuracy positioning algorithm employing an undifferenced observation model and applying ambiguity resolution. Successful ambiguity resolution is shown for a smartphone placed in a low multipath environment on the ground of a soccer field. For a rooftop open-sky test case with large multipath, ambiguity resolution was successful in 19 out of 35 data sets. Overall, the antenna calibration is demonstrated being an asset for smartphone-based positioning with ambiguity resolution, showing cm-level 2D root mean square error (RMSE).

In GNSS-based navigation onboard Low Earth Orbit (LEO) satellites, typical accuracy requirements are 10 cm and 0.1 mm/s for 3D position and velocity, respectively. Previous works have shown that such performance is achieved by including Galileo measurements in the estimation process. Here, we aim to evaluate the impact of employing State Space Representation (SSR) corrections, i.e., GNSS satellite orbit, clock, and biases, to be applied to the broadcast ephemerides. In this framework, the Precise Onboard Orbit Determination (P2OD) software (SW) tool developed at the University of Padua (UNIPD) is used to investigate the needs of onboard navigation. The UNIPD SW employs an Extended Kalman Filter (EKF) using a reduced-dynamics approach. The force model implemented is adapted to onboard processing, and empirical accelerations are included to take into account residual force mismodeling. Actual observation data from the LEO Sentinel-6A satellite are processed along with SSR corrections from the CNES service. Galileo-based solutions are compared to ground-based POD reference orbits. The analysis suggests that the use of SSR corrections provides sub-decimeter and below 0.1 mm/s accuracies in 3D position and velocity, respectively. Such results indicate a P2OD solution quality close to that achievable by adopting precise orbits and clocks.

The growing quality of smartphone-based Global Navigation Satellite Systems (GNSS) chipsets opens a new frontier for scientific research in positioning, navigation and timing ap- plications. The portability and affordability of these instruments could enhance the current GNSS receiver global network for atmospheric monitoring purposes. However, the quality of the measurements gathered from smartphones have not yet been fully assessed. In this paper, an analysis of the quality of smartphone-based Total Electron Content (TEC) mea- surements is performed. The primary focus of this work is to provide a general analysis on the potential of using smartphone observations for ionospheric sciences. Dual-frequency phase observations are used to measure the relative TEC. For this experiment, GPS L1/L5 and Galileo E1/E5a observations acquired with the Xiaomi Mi8 and Huawei Mate20 X smartphones were considered. Both devices are equipped with the Broadcom BCM47755 chipset, which enables GNSS dual-frequency measurements. More than 100 hours of phase observations at mid-latitude during a low solar activity period were gathered. Three differ- ent setup configurations were defined to assess the effects multipath or signal strength may have in the quality of the phase observations. In addition, to detect and discard unrealistic fluctuating phase observations, a quality-check was performed. In the results, good agree- ment between the slant TEC (sTEC) measurements from the smartphone and the sTEC obtained from a co-located geodetic receiver is presented. Furthermore, the amount and quality of observations discarded by the quality-check are reported, which emphasises the use of the signal strength to indicate the quality of phase observations. The results indicate that the C/N0 and multipath are important —when gathering the data from a geodetic antenna, around 80% of the collected data passed a quality threshold. However, collecting data with the addition of an attenuator, or directly from the smartphone antenna, reduced the valid data to below 50%. However, given the ease of use of a smartphone for data collection, even at 50% of data being usable, this shows potential as a useful course of TEC for ionospheric observations.

Earth’s gravity field can be reconstructed by adopting several techniques that involve data collected from satellite-, aircraft-, and ground-based measurements. Airborne gravimetry is a powerful tool for remote regions, like mountains or deserts, and for obtaining a higher spatial resolution than satellite gravity measurements. The German Absolute Aero Quantengravimetrie (AeroQGrav) project aims to build an airborne atom interferometer to fill gaps in regional geoid modelling and achieve precisions of down to 1 μm/s ² after 5 s of signal integration. In this manuscript, starting from the requirements, a spectral analysis of the sensor errors addresses the limiting factors of the project. In the sensor fusion process, separating the kinematic from the gravitational acceleration represents one of the main challenges of airborne gravimetry. Depending on the spatial resolution and frequency domain of interest, the successful achievement of the required measured gravity’s accuracy and precision may be limited by the spectral characteristics of the adopted kinematic sensors. An optimal simulation scenario is adopted to model the sensors and evaluate their noise contribution. Finally, it is presented how to exploit the fusion of the kinematic sensor measurements to retrieve the gravity signal at multiple frequencies of interest and precisions, overcoming the single-sensor limitations.