Integer ambiguity resolution is the key for achieving the highest accuracy with Precise Point Positioning (PPP) and for significantly reducing the convergence time. Unfortunately, due to hardware phase biases originating from the satellites and receiver, fixing the phase ambiguities to their correct integer number is difficult in PPP. Nowadays, various institutions and analysis centers of the International GNSS Service (IGS) provide satellite products (orbits, clocks, biases) based on different strategies, which allow PPP with integer ambiguity resolution (PPP-AR) for GPS and Galileo. We present the theoretical background and practical application of the satellite products from CNES, CODE, SGG, and TUG. They are tested in combined GPS and Galileo PPP-AR solutions calculated using our in-house software raPPPid. The numerical results show that the choice of satellite product has an influence on the convergence time of the fixed solution. The satellite product of CODE performs better than the following, in the given order: SGG_CODE, SGG_GFZ, TUG, CNES, and SGG_CNES. After the convergence period, a similar level of accuracy is achieved with all these products. With these satellite products and observations with an interval of 30 s, a mean convergence time of about 6 min to centimeter-level 2D positioning is achieved. Using high-rate observations and an observation interval of 1 s, this period can be reduced to a few minutes and, in the best case, just one minute.

With the availability of low-cost, mass-market dual-frequency GNSS (Global Navigation Satellite System) receivers, standalone processing methods such as Precise Point Positioning (PPP) are no longer restricted to geodetic-grade GNSS equipment only. However, with cheaper equipment, data quality is expected to degrade. This same principle also affects low-cost GNSS antennas, which usually suffer from poorer multipath mitigation and higher antenna noise compared to their geodetic-grade counterparts. This work assesses the quality of a particular piece of low-cost GNSS equipment for real-time PPP and high-rate dynamic monitoring applications, such as strong-motion seismology. We assembled the u-blox ZED-F9P chip in a small and light-weight data logger. With observational data from static experiments—which are processed under kinematic conditions—we assess the precision and stability of the displacement estimates. We tested the impact of different multi-band antenna types, including geodetic medium-grade helical-type (JAVAD GrAnt-G3T), as well as a low-cost helical (Ardusimple AS-ANT2B-CAL) and a patch-type (u-blox ANN-MB) antenna. Besides static tests for the assessment of displacement precision, strong-motion dynamic ground movements are simulated with a robot arm. For cross-validation, we collected measurements with a JAVAD SIGMA G3T geodetic-grade receiver. In terms of precision, we cross-compare the results of three different dual-frequency, real-time PPP solutions: (1) an ambiguity-float solution using the Centre National d’Études Spatiales (CNES) open-source software, (2) an ambiguity-float and an AR (ambiguity-resolved) solution using the raPPPid software from TU Vienna, and (3) and a PPP-RTK solution using the u-blox PointPerfect positioning service. We show that, even with low-cost GNSS equipment, it is possible to obtain a precision of one centimeter. We conclude that these devices provide an excellent basis for the densification of existing GNSS monitoring networks, as needed for strong-motion seismology and earthquake-early-warning.

Precise Point Positioning (PPP) has proven to be a powerful GNSS positioning method used for various scientific and commercial applications nowadays. We present a flexible and user-friendly software package named raPPPid suitable for processing single to triple-frequency GNSS observations in various PPP approaches (e.g., ionospheric-free linear combination, uncombined model), available under https://github.com/TUW-VieVS/raPPPid. To tune the PPP procedure, the user can select from many satellite products, models, options, and parameters. This way, the software raPPPid can handle high-to-low quality observation data ranging from geodetic equipment to smartphones. Despite significant improvements, the convergence time of PPP is still a major topic in scientific research. raPPPid is specially designed to reduce the convergence period with diverse implemented approaches, such as PPP-AR or ionospheric pseudo-observations, and to offer the user multiple plots and statistics to analyze this critical period. Typically, raPPPid achieves coordinate convergence times of around 1 min or below with high-quality observations and ambiguity fixing. With smartphone data and a simplified PPP approach, a 2D position accuracy at the one-meter level or below is accomplished after two to three minutes.

Propagation delays of GNSS signals caused by the ionosphere can range up to several meters in zenith direction and need to be corrected. Geodetic receivers observing at two or more frequencies allow the mitigation of the ionospheric effects by forming linear combinations. However, single frequency users depend on external information. The ionosphere delay model Regiomontan developed at TU Wien is a regional ionospheric delay model providing high accuracy information with a latency of only a few hours. The model is based on dual-frequency phase observations of a regional network operated by EPOSA (Echtzeit Positionierung Austria) and partners. The corrections cover a geographical extent for receiver positions within Austria and are provided in the standardized IONEX format. The performance of Regiomontan as well as its application in Precise Point Positioning (PPP) were tested with our in-house PPP software raPPPid using the so-called uncombined model with ionospheric constraint. Various tests, e.g., analyzing the coordinate convergence behavior or the difference between estimated and modeled ionospheric delay, proving the high level of accuracy provided with Regiomontan. We conclude that Regiomontan performs at a similar level of accuracy as IGS final TEC maps, but with explicitly reduced latency.

Water vapor is one of the most variable components in the earth's atmosphere and has a significant role in forming clouds, rain and snow, air pollution, and acid rain. Therefore, increasing the accuracy of estimated water vapor can lead to more accurate predictions of severe weather, upcoming storms, and natural hazards. In recent years, GNSS has turned out to be a valuable tool for remotely sensing the atmosphere. In this context, GNSS tomography evolved to an extremely promising technique to reconstruct the spatiotemporal structure of the troposphere. However, locating dual-frequency (DF) receivers with a spatial resolution of a few tens of kilometers sufficient for GNSS tomography is not economically feasible. Therefore, in this research, the feasibility of using single-frequency (SF) observations in GNSS tomography as an alternative approach has been investigated. The algebraic reconstruction technique (ART) and the total variation (TV) method are examined to reconstruct a regularized solution. The accuracy of the reconstructed water vapor distribution model using low-cost receivers is verified by radiosonde measurements in the area of the EPOSA (Echtzeit Positionierung Austria) GNSS network, which is mostly located in the east part of Austria for the period DoY 232–245, 2019. The results indicate that irrespective of the investigated ART and TV techniques, the quality of the reconstructed wet refractivity field is comparable for both SF and DF schemes. However, in the SF scheme the MAE with respect to the radiosonde measurements for ART + NWM and ART + TV can reach up to 10 ppm during noontime. Despite that, all statistical results demonstrate the degradation of the retrieved wet refractivity field of only 10–40% when applying the SF scheme in the presence of the initial guess.