Orals: Tue, 29 Apr | Room K2
Precise point positioning real-time kinematic (PPP-RTK), by capitalizing on its state-space representation (SSR) and its associated flexibility, is naturally emerging as one of the prevalent Global Navigation Satellite System (GNSS) techniques for high-precision positioning. The determination of unbiased ambiguity-resolved positional parameters becomes possible once single-receiver users get access to SSR corrections. However, the fact that such SSR corrections are often estimated in a recursive manner, based on a set of assumptions and a singularity-basis (S-basis) choice made in an arbitrary fashion by the correction provider (i.e., a GNSS network), may lead to serious pitfalls which the PPP-RTK user should be aware of when interpreting the delivered corrections. In this contribution, we will present the intricacies inherent in multi-epoch filtered PPP-RTK corrections and address the consequence of the corrections’ dependency on the provider’s S-basis. Through illustrative examples, it is shown how one can be misled by merely analyzing the estimable satellite clock solutions’ temporal characteristics, and how the distributional properties of the satellite phase bias solutions can be affected in case only their fractional part is delivered, contrary to the users’ usual expectation of being equipped with Gaussian-distributed phase biases. Next to this analysis, the important roles played by the correction latency and time correlation are addressed in both ambiguity-resolved positioning and the associated ambiguity-float and -fixed confidence information reported by the user estimation process.
How to cite: Psychas, D., Khodabandeh, A., and Teunissen, P. J. G.: On the intricacies of multi-epoch filtered PPP-RTK corrections and their impact on GNSS ambiguity resolution, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-19300, https://doi.org/10.5194/egusphere-egu25-19300, 2025.
In recent decades, Precise Point Positioning (PPP) has become a well-established GNSS positioning method that is used in various applications. PPP is characterized by the use of precise satellite products (satellite orbits, clocks, and biases) combined with the accurate modeling of various error sources and elaborate algorithms. This way, PPP allows us to achieve position accuracies at the centimeter or even millimeter level. Nowadays, several institutions provide high-quality multi-GNSS satellite products through the International GNSS Service (IGS). These modern satellite products enable, for example, integer ambiguity fixing and incorporating observations from multiple GNSS in the PPP solution, typically enhancing the PPP performance.
In this contribution, we provide an overview of the currently available multi-GNSS satellite products and discuss their potential benefits of using 2+ frequencies and alternatives to the ionosphere-free linear combination. These methods are considered advantageous for improving PPP performance, particularly regarding convergence time. We present PPP results using GPS, GLONASS, Galileo, and BeiDou observations and satellite products from different institutions, focusing on integer ambiguity resolution (PPP-AR). Additionally, we test the combined multi-GNSS product developed by the GNSS Research Center at Wuhan University as part of the IGS PPP-AR Pilot Project. We evaluate the resulting coordinate accuracy, convergence behavior, and ambiguity fixing rates. The PPP investigations are conducted with the open-source raPPPid, part of the Vienna VLBI and Satellite Software (VieVS PPP).
How to cite: Wareyka-Glaner, M. F. and Möller, G.: Enhancing PPP Performance with Multi-GNSS Satellite Products and Integer Ambiguity Resolution, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15232, https://doi.org/10.5194/egusphere-egu25-15232, 2025.
Tropospheric delay and multipath effect are two key errors that are difficult to be accurately corrected in Global Navigation Satellite System (GNSS) Precise Point Positioning Ambiguity Resolution (PPP-AR). The tropospheric residuals due to imperfect modeling can be significant in harsh environments, like in regions with complex terrain and during extreme weather. As the tropospheric delay and multipath effect are coupled in the unmodeled errors, the tropospheric residuals could be misunderstood as multipath. Therefore, accurate correction of the tropospheric delay is crucial for estimating the multipath. However, the coupling effect was not properly considered in previous studies. We propose a refined joint troposphere-multipath hemispherical map (TMM), by constructing a refined troposphere hemispherical map (THM) and an improved multipath hemispherical map (C-TMHM). We use ray-tracing and meteorological data to construct THM correction tables, while tropospheric delays in PPP-AR are corrected by retrieving the corresponding satellite tropospheric delay estimates to obtain "cleaner" multipath model values. Results show that the tropospheric THM model reduces GNSS residuals from about 10 mm to 2 mm at low-elevation (7°~30°) compared to the Vienna Mapping Functions 3 (VMF3). Because that the topographic complexity and the rapid variations in atmospheric water vapor are not adequately considered by simply using the elevation-dependent mapping function and horizontal gradients. In particular, part of the tropospheric residuals in the low-elevation are likely to be misinterpreted as multipath. Compared with multi-GNSS PPP-AR performance using traditional model (VMF3 and uncorrected multipath), the proposed TMM (THM and C-TMHM) model improves the positioning accuracy by 32.12% and 36.18% under the cases of complex terrain and extreme weather, respectively, while shortens the convergence time by 33.04% and 30.7%.
How to cite: Lu, R., Zhang, M., Li, Z., Yuan, P., and Jiang, W.: Improved multi-GNSS PPP-AR performance through refined tropospheric and multipath models, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-5095, https://doi.org/10.5194/egusphere-egu25-5095, 2025.
Since early 2023, the Galileo High Accuracy Service (HAS) has been officially providing free corrections for Precise Point Positioning (PPP). The HAS is structured into two service levels. The first level (SL1), currently available worldwide, delivers orbit and clock corrections along with code biases for three GPS frequencies (L1, L2C, L5) and four Galileo frequencies (E1, E5a, E5b, E6). The second level (SL2), which is planned to operate exclusively within the European Coverage Area (ECA), will include atmospheric corrections.
In January 2023, the Service Definition Document (SDD) established the targeted HAS accuracy at 15 centimeters horizontally and 20 centimeters vertically, with a confidence level of 68% for static users outside the Pacific region.
An initial evaluation of the HAS performance was conducted between Day of Year (DOY) 92 and DOY 153 of 2023. In terms of correction availability, the service supports an average of 16 to 21 corrected satellites (GPS and Galileo together), depending on the user’s location. Regarding accuracy, the corrections improved the Signal-In-Space Range Error (SISRE) by 54% for Galileo and 61% for GPS, when compared to broadcast ephemeris.
To validate the HAS corrections, Precise Point Positioning (PPP) was performed using data from 132 Regional Reference Frame Sub-Commission for Europe (EUREF) stations across Europe. The analysis was conducted in static mode with a dual-constellation configuration (GPS/Galileo), a 30-second sampling interval, float ambiguities, and uncombined measurements. The results achieved a 68% accuracy of 4.4 centimeters horizontally and 4.7 centimeters vertically.
These EUREF stations were subsequently employed to generate atmospheric corrections, specifically ionospheric and tropospheric, to test the second service level. Three station networks with varying densities were constructed, consisting of 132, 49, or 34 stations. After an evaluation of these atmospheric corrections coming from these networks, a PPP positioning over 64 other EUREF stations has been performed. This positioning was carried out in kinematic mode, using the same dual-constellation setup, 30-second sampling, float ambiguities, and uncombined measurements.
The results demonstrated that atmospheric corrections had a significant impact on positioning performance. The 68% accuracy improved by 43% horizontally and 47% vertically. Furthermore, the horizontal convergence time was reduced by half and is achieved in 60 minutes instead of 127 minutes. It highlights the potential benefits of the second service level for real-time applications.
ACKNOWLEDGEMENTS
We would like to acknowledge Munich Aerospace for the scholarship that made this study possible.
REFERENCES
[1] EUSPA, “Galileo high accuracy service service definition document (HAS SDD),” European Union, Tech. Rep., 2022.
How to cite: Parra, C., Hugentobler, U., Pany, T., and Baumann, S.: Performance Assessment of Galileo High Accuracy Service for PPP and Atmospheric Correction Impact in 2023, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6826, https://doi.org/10.5194/egusphere-egu25-6826, 2025.
Low Earth Orbit Positioning Navigation and Timing (LEO-PNT) is an emerging satellite navigation concept to augment current Global Navigation Satellite Systems by placing satellites close to Earth, at around 600-1200 km altitude. This proximity leads to a rapid change in satellite geometry, which is mainly expected to reduce the convergence time of real-time precise positioning. To realize the benefits of LEO’s faster dynamics, the positions and clock offsets of the LEO-PNT satellites must be known with a high accuracy and low latency. In existing GNSS constellations deployed in Medium Earth Orbit (MEO), global networks of ground stations are generally used to estimate the satellite positions and clock offsets, which are then uplinked to the satellites for broadcast to users. This same approach for LEO-PNT systems would require an extensive ground network due to their closer proximity to Earth. Instead, on-board GNSS-based Precise Orbit Determination (POD) for LEO-PNT satellites offers a feasible alternative.
This study investigates the impact on ground positioning users when performing on-board POD for LEO-PNT satellites. The numerical assessment consists of two parts: in the first part we focus on the on-board POD results by using Sentinel-6A real-world data from DOY 118-124 in 2024 including both GPS and Galileo observations. A reduced-dynamics extended Kalman filter POD approach with degraded dynamical models is used to replicate on-board processing conditions. Various types of GNSS corrections are tested to assess the POD accuracy achievable on board. 3D RMS orbit errors of 2.8 cm, 4.8 cm, 9.9 cm, and 15.2 cm are obtained in the numerical POD computations respectively based on the CODE MGEX final products (COD), the CNES Real-Time products (CRT), the Galileo High Accuracy Service corrections (HAS), and the broadcast ephemerides (BRD). Moreover, we compare the estimated receiver clock offsets with respect to a precise reference clock solution computed in a batch-least squares approach without orbital model degradation.
In the second part, we focus on the impact of these LEO orbit and clock errors in an end-to-end simulation of kinematic float-PPP for a ground user. A LEO space segment of 28 satellites was simulated to augment the cases of GPS only, Galileo only, and GPS+Galileo, while considering different product configurations. The results showed that a LEO space segment with CRT-level orbit and clock errors could consistently improve the convergence time as compared to each corresponding stand-alone MEO case. For a HAS ground user using GPS and Galileo, the LEO with HAS-level orbit errors achieved 20 cm horizontal convergence under 3 minutes when clock errors were neglected. At the same time, the overall positioning accuracy results did not show significant improvement nor degradation from including the LEO space segment. Based on our preliminary findings, the expected benefits of LEO-PNT augmentation are only possible when sufficiently accurate orbits and clocks are estimated and provided to users. Still, the impact of the correction latency and availability shall be further investigated in future works.
How to cite: Oduber, J., Massarweh, L., and van den IJssel, J.: Impact of on-board satellite orbits and clocks estimation for LEO-PNT ground positioning, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-19075, https://doi.org/10.5194/egusphere-egu25-19075, 2025.
To realize the various benefits brought by Low Earth Orbit (LEO) satellites in single-receiver high-precision GNSS-based Positioning Navigation and Timing (PNT) services, LEO satellite orbits and clocks need to be processed and delivered to users in real-time with precision of a few centimeters. While post-processing of cm-level LEO satellite orbits and clocks can be widely achieved, real-time processing faces various Challenges. When the number of LEO satellites increases, the observation data downlinked to the processing center may experience large and complicated discontinuities and incompleteness depending on the downlinking strategies. Even with the observations downlinked in real-time, the LEO satellite clock precision tends to be very sensitive to the continuity and quality of the GNSS real-time products. This study first introduces the procedure for ground-based cm-level real-time LEO satellite Precise Orbit Determination (POD), including near-real-time POD, short-term prediction, and ephemeris fitting/broadcasting. Next, the short-term predicted orbits and long-term predicted clocks of LEO satellites are introduced and properly constrained in filter-based real-time LEO satellite clock determination to achieve a precision of about 0.2 ns. Strategies to deal with sub-optimal observation data and GNSS products are explained. With the proposed methods, a Signal-In-Space Ranging Error at sub-dm to 1 dm can be achieved in practice.
How to cite: Wang, K., Xie, W., Chen, B., Liu, J., Wu, M., El-Mowafy, A., and Yang, X.: Real-time LEO satellite precise orbit and clock determination for augmenting GNSS: Strategies and Challenges, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-2002, https://doi.org/10.5194/egusphere-egu25-2002, 2025.
Positioning, Navigation, and Timing (PNT) services have delivered significant benefits to modern society. Currently, much of our PNT needs are fulfilled by Global Navigation Satellite Systems (GNSS). However, GNSS is facing a series of challenges, including signal blockage in dense urban areas, bush land and indoors and susceptivity to radio frequency interference. There is a urgent global demand for backup solutions to address the reliability of GNSS. The substantial expansion and massive deployment of small satellites have catalyzed the development of Low Earth Orbit (LEO) communication constellations have been rapidly developed, such as SpaceX’s Starlink and China Satellite Network communication system. In the near future, these constellations are projected to comprise tens of thousands of satellites. These satellites present significant advantages over GNSS, such as operating at higher frequencies (over 10 GHz) and providing wider signal bandwidths (several hundred MHz), along with superior signal quality. Such attributes make them viable candidates for PNT solutions and open up opportunities to utilize their signals as alternative sources for PNT applications.
Due to unknown structure of commercial LEO communication signals, most positioning methods based on LEO communication satellites rely on Doppler measurements. However, Doppler-based positioning is challenging for high-dynamic objects and high-precision positioning, as it requires integrating over significant periods for range difference measurements and imposing height constraints. Previous experience suggests that positioning with ranging measurements significantly outperforms Doppler-based methods in terms of accuracy and applicability. Unlike GNSS, which has publicly available signal structures for obtaining range, LEO communication signal structures are not disclosed. Therefore, this study aims to develop algorithms for estimating ranging measurements derived from LEO communication signals with unknown signal structures.
The downlink signals of LEO communication systems (i.e. Starlink) are simulated. By employing the Primary Synchronization Signal (PSS) and Secondary Synchronization Signal (SSS) sequences as ranging sequences, we facilitate the coarse acquisition of communication satellites. Then, a Delay Lock Loop (DLL) is developed to track the PSS and SSS sequences to continuously estimate signal delays. Additionally, we exploit the benefits of Orthogonal Frequency-Division Multiplexing (OFDM) modulation in LEO communication signals by designing the multiple Phase Lock Loops (PLLs) to track various subcarriers. By applying the phase difference across different frequencies, we can construct artificial wavelengths at the meter level, akin to wide-lane combinations in GNSS. This approach can reduce the ambiguity in the integer number of wavelengths between the satellite and the receiver, which is a notable challenge in carrier measurements of high-frequency LEO communication signals. This study introduces two ranging schemes: one based on time delay estimation via synchronization sequences and the other on carrier phase tracking using multiple PLL. When combined with two-line element (TLE) files, these schemes enable a positioning service based on LEO communication satellites.
How to cite: ding, M., chen, W., wang, J., yang, Y., mi, X., and luo, H.: Range estimation method of LEO communication opportunity signals for alternative PNT , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9788, https://doi.org/10.5194/egusphere-egu25-9788, 2025.
How to cite: Steigenberger, P., Thoelert, S., and Montenbruck, O.: Evaluation of Galileo FOC Reference Antenna Patterns, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-4275, https://doi.org/10.5194/egusphere-egu25-4275, 2025.
Since 2016, Android smartphones have allowed access to the raw GNSS data, leading to significant improvements in positioning accuracy. Modern devices now support dual-frequency GNSS and multiple satellite systems, making positioning more reliable. Despite significant efforts in GNSS smartphone positioning, including using the Galileo constellation, several important issues still need to be addressed. Galileo signals have more complex modulation schemes compared to GPS signals. Practical tests show that after a short period, Galileo measurements' status may change from 'TOW Decoded' to 'E1C 2nd Code' status, where TOW represents the GNSS time of week. The receiver can stay on the 'E1C 2nd Code' status for several minutes. Some Galileo-ready chips track the data component to decode the navigation message. Once the ephemerides and clock data are decoded, they switch to tracking the E1C (pilot component), resulting in the 'E1C 2nd Code' status and ambiguous pseudoranges. In the current Galileo tracking approach, some satellites remain in 'TOW Known' or 'TOW Decoded' status for over an hour, while others switch to 'E1C 2nd Code Lock', resulting in ambiguous pseudoranges. The algorithm used to determine the tracking status for each satellite remains unclear. The white paper published by the European GNSS Agency’s (GSA) recommends checking the Galileo tracking status and highly advises using Galileo measurements only when in the E1C 2nd Code status.
In this research, we will show that a 4 ms jump is still observed in some datasets, even though the tracking status is E1C 2nd Code. This confirms that verifying the signal tracking status alone is insufficient, as 4 ms jumps in the data can still occur despite this check. During these "jump epochs," erroneous measurements can adversely affect positioning accuracy. To investigate this issue, data collected by the Xiaomi Mi8 and Google Pixel 8 Pro devices are used. The results indicate that these jumps vary between devices and over time. The results also show that these jumps still occur, even though the tracking status is E1C 2nd Code.
This 4 ms jump has also been addressed by Galluzzo et al. (2018) during the 2018 IPIN conference. They proposed a straightforward method to correct the pseudorange by detecting jumps through the difference between two consecutive epochs. If the difference is around 4 ms, the subsequent pseudoranges are adjusted accordingly. Although the theory behind this method is straightforward and effective in many cases, it cannot detect all jumps, for example, when those satellites first appear or when the pseudorange is missing. In this research, we employ the Observation Minus Calcaulation (OMC) to solve this issue and find the undetected 4 ms jumps. Finally, we investigate the accuracy of the kinematic data from Xiaomi Mi8 and Google Pixel 8 Pro devices with and without corrections for the 4 ms jumps. The results showed performance improvement in terms of the root mean square (RMS) and the 50th percentile of the horizontal positioning error after applying the correction for the 4 ms jump in Galileo measurements.
How to cite: Zangenehnejad, F., Elsheikh, M., Liu, F., and Gao, Y.: Investigating Galileo Signal Tracking Challenges in Smartphones, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-20749, https://doi.org/10.5194/egusphere-egu25-20749, 2025.
The study of signatures in the ionospheric total electron content (TEC) related to seismic events such as earthquakes and tsunamis, has predominantly focused on significant, high-impact occurences, such as the 2004 Sumatra earthquake and tsunami (Mw 9.2) [2] or the 2011 Tohoku-Oki event (Mw 9.0) [3]. These generate clear signatures in TEC time series, that can offer valuable insights in enhancing early warning systems for tsunamis. However, despite the knowledge gained from these significant events, there remains a crucial gap in the literature concerning smaller-scale seismic events presenting Mw7 and few meters high tsunami waves. Indeed, while earthquakes with Mw around 7 are not considered small in a general sense, they are relatively minor in terms of their ability to generate pronounced ionospheric perturbations. Nevertheless, their study is equally important due to their potential for significant impact on humans and the environment. This has been demonstrated in seismic regions like the Mediterranean Sea, where the tsunami waves are amplified by narrow straits and coastal configurations, making even smaller events highly destructive. This underscores the critical need for studies focused on smaller yet impactful events to improve real-time tsunami early warning systems.
Motivated by the seismic nature of the Mediterranean region, marked by small-scale earthquakes and tsunamis from a ionospheric point of view,we carried out the study related to the detection of the small signatures generated in the ionosphere by the Samos earthquake and tsunami that occurred on 30 October2020 (Mw 7.0), causing tsunami waves up to 3 m. This study examines Global Navigation Satellite System (GNSS) data to analyze the resulting ionospheric disturbances in total electron content (TEC) measurements. We detected TEC variations of up to 0.3 TECU, associated with the propagation of internal gravity waves (IGWs) triggered by the small tsunami. By comparing the IGWs' arrival times in the ionosphere with tsunami wave arrivals at tide gauges, we found that optimal ionospheric TEC observation geometries detected the tsunami's presence before it reached the Kos and Heraklion coastlines. Our findings demonstrate that even small TEC variations can complement existing tsunami early warning systems. This is particularly valuable in the Mediterranean region, where such phenomena remain underexplored. Integrating TEC data with traditional seismic sensors and sea level measurements can enhance early warning systems, improving their capacity to detect and mitigate the effects of small but significant tsunamis.
The results are published in Fuso & Ravanelli (2024) [1].
[1] Fuso, F., & Ravanelli, M. (2024). Probing the ionospheric effects of the 2020 Aegean Sea earthquake: Leveraging GNSS observations for tsunami early warning in the Mediterranean. Journal of Geophysical Research: Space Physics, 129(12), e2024JA032946.
[2] Occhipinti, G., Lognonné, P., Kherani, E. A., & Hébert, H. (2006). Three‐dimensional waveform modeling of ionospheric signature induced by the 2004 Sumatra tsunami. Geophysical research letters, 33(20).
[3] Occhipinti, G., Rolland, L., Lognonné, P., & Watada, S. (2013). From Sumatra 2004 to Tohoku‐Oki 2011: The systematic GPS detection of the ionospheric signature induced by tsunamigenic earthquakes. Journal of Geophysical Research: Space Physics, 118(6), 3626-3636.
How to cite: Fuso, F. and Ravanelli, M.: Investigating Ionospheric Disturbances from the 2020 Samos Earthquake and Tsunami: Advancing GNSS-Based Tsunami Early Warning in the Mediterranean, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10748, https://doi.org/10.5194/egusphere-egu25-10748, 2025.
The growing interest of the GNSS community in computing GNSS series using the iPPP (Precise Point Positioning with integer ambiguity resolution) mode with the GINS software and the products of the CNES/CLS analysis center (GRG products) culminated in 2022 with the SPOTGINS project. This initiative enables several research laboratories to cooperate in processing a global network of stations, benefiting from the expertise of the IGS analysis center and the advanced quality of the GRG products.
This standardization and collaboration require a unified computational strategy, involving the same version of the GINS software, identical configurations (products, corrections, models, constellations), and consistent metadata. Currently, daily station positions are computed using GPS and Galileo constellations, using the “G20” orbits and clocks from the IGS CNES-CLS based on ITRF2020, FES2014b ocean tidal loading and VMF1 mapping functions.
SPOTGINS started in 2022 with the collaboration between the OMP in Toulouse, the EOST in Strasbourg and the LIENSs in La Rochelle, whose massive calculations with GINS were already being done for several years. In 2023 and 2024, other groups expressed interest in joining SPOTGINS: the GeF/Cnam in Le Mans, the IPGP/IGN in Paris and the OSUG/ISTerre in Grenoble. Each member pursues different scientific objectives, but all contribute collectively to the dissemination of PPP series for the community through the Geodesy Plotter of the FormaTerre data and service hub.
How to cite: Boy, J.-P., Fériol, F., Gravelle, M., Janex, G., Loyer, S., Nahmani, S., Nicolas, J., Pollet, A., Sakic, P., Santamaría-Gómez, A., and Tsapong-Tsague, A.-B.: SPOTGINS: A New Global GNSS Daily iPPP Solution Derived Using GINS software , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-12545, https://doi.org/10.5194/egusphere-egu25-12545, 2025.
PRIDE PPP-AR is a Global Navigation Satellite System (GNSS) Precise Point Positioning (PPP) software specifically designed for applications in Earth sciences. Since its initial release in 2019, the software has been updated to version 3.1. The core strength of PRIDE PPP-AR lies in its PPP-AR processing capabilities with arbitrary dual-frequency ionosphere-free combinations. It is also featured by low Earth orbit satellite solutions, multipath mitigation, epoch-by-epoch constraints in segmented processing mode, multi-day continuous processing, and ocean tide loading corrections without ocean tide coefficients. Furthermore, PRIDE PPP-AR is compatible with the three major operating systems: Linux, Windows, and macOS, providing great convenience for early-career researchers, facilitating easier learning and usage.
Tests conducted using 511 IGS reference stations in January 2018 showed that, when compared with IGS solutions, PRIDE PPP-AR can achieve millimeter-level static solutions and tropospheric delays, and centimeter-level dynamic solutions, with an average fix rate of 95%. In the fields of geodesy and Earth sciences, the high-precision positioning capabilities of PRIDE PPP-AR make it a powerful tool for studying Earth dynamics, crustal deformation, and seismic monitoring. Additionally, its performance on high-dynamic platforms such as aerial photogrammetry and shipborne gravimetry is outstanding, providing technical support for scientific research and engineering practices in related fields. The new version of PRIDE PPP-AR will be able to fully utilize the advantages of GNSS modernization, enhancing high-precision positioning accuracy in a broader range of research areas.
How to cite: Geng, J. and Wen, Q.: PRIDE PPP-AR: mitigating multipath and day-boundary discontinuities for geodesy and geophysics, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-4789, https://doi.org/10.5194/egusphere-egu25-4789, 2025.
The BDS-3 provides signals at six different frequency bands, which are expected to improve the precision and convergence speed of Precise Point Positioning (PPP). To fully utilize the full-frequency data from BDS-3, three PPP function models were constructed: the six-frequency undifferenced and non-combined model (UC6), the single-layer six-frequency ionosphere-free model (IF6-1), and the six-frequency ionosphere-free dual-combination model (IF6-2).For the six-frequency undifferenced and non-combined model (UC6), the IFB (Inter-frequency Bias) processing strategy was studied, and the impact of three commonly used processing strategies on IFB estimation was analyzed. The results showed that when using constant models and random walk models, the estimated IFB values were similar, while the white noise model, despite slight fluctuations in the estimated IFB, exhibited a trend consistent with the other two models.The positioning experimental results indicated that the positioning accuracy after static convergence for the UC6, IF6-1, and IF6-2 models was similar. The horizontal mean accuracy was 1.36, 1.35, and 1.39 cm, respectively, and the vertical accuracy was 1.42, 1.45, and 1.63 cm. In dynamic mode, the horizontal accuracy was 4.04, 4.10, and 4.12 cm, and the vertical accuracy was 5.52 cm, 5.19 cm, and 5.02 cm.In terms of convergence time, the IF6-1 model showed superior static and dynamic convergence performance compared to the UC6 and IF6-2 models. Further analysis compared the receiver clock offsets, inter-frequency biases, and zenith wet delays between the different models. The receiver clock offset time series from all three models were consistent, and the inter-frequency bias for the same receiver model remained stable throughout the day. Additionally, the zenith wet delay estimates from all three models tended to converge after the process reached steady-state.
How to cite: Wang, L., Ma, C., Cui, B., Huang, G., and Zhang, Q.: Performance Analysis and Comparison of BDS-3 All-frequency Precise Point Positioning, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-8092, https://doi.org/10.5194/egusphere-egu25-8092, 2025.
Multipath continues to pose a significant challenge for the Global Navigation Satellite System (GNSS) technique in achieving precise Precise Point Positioning (PPP). Sidereal Filtering (SF) and multipath hemispherical map (MHM) represent common methods for mitigating multipath by leveraging satellite temporal and spatial repeatability. However, the effectiveness of these approaches relies heavily on the quality of the multipath correction model derived from preceding PPP residuals, which often contains product and parameter estimation errors. These errors can notably compromise the accuracy and reliability of multipath mitigation efforts. We propose an innovative method for extracting multipath based on a refined error separation strategy and mitigating multipath with SF. This method involves decomposing PPP residuals into multiple reconstructed components (RCs) using the multi-channel singular spectrum analysis (MSSA) technique and subsequently isolating multipath by reconstructing RCs exhibiting strong temporal repeatability. Extensive experiments with a 28-day dataset from 20 multi-GNSS stations demonstrated the effectiveness of our method. Compared to the conventional wavelet-based SF method, the proposed approach improved PPP accuracy by 23%, 20%, and 18% in the East, North, and Up directions, respectively, and by 18%, 16%, and 15% compared to the MHM method. Results also reveal that PPP residuals can be decomposed into multipath, high-frequency noise, common-mode error (CME), and site-specific errors. The last two components, which are non-repeatable in time and space, pose limitations on the effectiveness of conventional SF and MHM strategies in addressing multipath effects.
How to cite: Li, X., Wang, L., Ding, X., Zhang, Q., Qu, X., and Shu, B.: New Insights of Accurate Multipath Mitigation for Multi-GNSS PPP Using Refined Multipath Extraction Strategy, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-2304, https://doi.org/10.5194/egusphere-egu25-2304, 2025.
Despite the increasing number of satellites in multi-constellation GNSS, signal availability and quality remain significant problems in urban and forested environments. Field obstacles such as buildings and dense vegetation can lead to severe multipath issues. Various methods have been developed to mitigate multipath effects on measurement results, including optimizing antenna placement, selecting appropriate antenna and receiver types, and employing advanced post-processing techniques. However, these efforts have been unable to completely eliminate multipath interference, which can greatly affect positioning accuracy. The authors of this presentation have developed a tool that helps identify and remove reflected signals from measurement data sets. This tool, called GNSS MPD, was developed to predict satellite signal obstructions. It considers Line of Sight (LOS) vectors between specific locations and satellite positions and obstacle models derived from airborne LiDAR data. The LiDAR data is automatically acquired from geoportal.gov.pl, enabling the generation of an approximate terrain cover model. Satellite obstructions are validated using a ray-casting method. As part of testing the developed platform, the authors designed two experiments. The first experiment is a comparative analysis between satellite visibility scenarios obtained from GNSS MPD calculations and hemispherical photography. The second study involves performing positioning using information regarding the satellite visibility from GNSS MPD software. As part of this study, five 24-hour measurement sessions were conducted in a highly urbanized area. Based on the receiver's approximate position, satellite visibility scenarios are generated using the developed platform. Static positioning measurements were performed in the experiment, yielding two sets of results: one based on raw receiver observations and the other incorporating visibility scenarios from the platform to adjust the observation files. The test results demonstrate improvements in both accuracy and the success rate of position determination.
How to cite: Tomaszewski, D., Rapiński, J., Janowski, A., and Pelc-Mieczkowska, R.: Enhancing GNSS Positioning Accuracy in Challenging Environments: Development and Validation of a Multipath Prediction Tool, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-2818, https://doi.org/10.5194/egusphere-egu25-2818, 2025.
As urban populations continue to grow, the demand for precise positioning has become increasingly critical for various applications, including navigation, location-based services (LBS), transportation, delivery, and logistics. Global Navigation Satellite Systems (GNSS) are widely utilized for positioning; however, they encounter significant challenges in urban canyons, where signal obstructions and reflections can degrade positioning accuracy by tens to hundreds of meters.
To address these challenges, existing consistency check methods have been developed to detect and exclude erroneous observations from multiple GNSS constellations, thereby improving performance in open or low-density urban environments. Nevertheless, high-density urban areas present difficulties, as the majority of GNSS signals are often compromised by non-line-of-sight (NLOS) reception and multipath interference. While the integration of inertial sensors with GNSS technology has shown effectiveness in addressing GNSS outages, the accumulation of drift errors in pedestrian dead reckoning (PDR) still hinder performance in dense urban settings where GNSS solutions are consistently unreliable.
In this study, we propose a novel approach that tightly integrates PDR and GNSS data in the measurement domain to effectively identify fault-free measurements amidst a backdrop of contaminated signals. We introduce a multi-epoch smoothing algorithm designed to enhance positioning accuracy. Our method employs a two-stage consistency check algorithm to mitigate multipath effects, incorporating both satellite quality assessments and grid quality evaluations based on raw GNSS observations and inertial sensor data. Notably, we leverage time-series residuals from multi-epoch GNSS observations to identify fault-free measurements, moving beyond the limitations of single-epoch data. Additionally, grid quality is evaluated based on the discrepancies in residuals among high-quality satellites. To bolster the robustness and reliability of positioning, our algorithm integrates a positioning scheme that utilizes weight smoothing based on multi-epoch grid mapping and outlier mitigation through density-based spatial clustering of applications with noise (DBSCAN) clustering.
Field experiments conducted in typical urban environments in Hong Kong, utilizing a standard smartphone as the receiver, demonstrated substantial improvements over conventional consistency check methods and chip outputs. Our findings reveal that traditional consistency check methods underperformed compared to chip outputs in dense urban areas. In contrast, the proposed method significantly enhanced positioning accuracy across all trials, achieving accuracies ranging from 2m to 10m, compared to chip outputs that varied from 5m to 58m. The proposed approach yielded an improvement rate of 50% to 88% across different urban densities.
This innovative method is compatible with most consumer-grade devices, requiring no additional hardware, thereby offering enhanced convenience and intelligence for urban residents. Its ease of implementation across various brands and real-time operation with low computational load make it a versatile solution for improving positioning accuracy in complex urban environments.
How to cite: luo, H., Yang, Y., Mi, X., Ding, M., and Chen, W.: Enhancing GNSS Positioning Accuracy in Urban Canyons: A Multi-Epoch Residual-Based Consistency Check and IMU-GNSS Tight Coupling Approach, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-14893, https://doi.org/10.5194/egusphere-egu25-14893, 2025.
In precise point positioning, the fixed ambiguity can significantly improve the positioning accuracy of PPP and accelerate the convergence speed to a certain extent. The quality of phase deviation products directly determines the ambiguity resolution effect, and then affects the positioning performance of PPP-AR. At present, CNES is the only analysis center that publicly provides real-time observable-specific signal bias products (OSB). In order to promote the practical application of RT PPP-AR, it is necessary to evaluate the data quality and PPP-AR positioning performance of real-time OSB products provided by CNES. In this paper, the observation data of 42 MGEX stations from May 1, 2023 (DOY 121) to May 10, 2023 (DOY 130) are selected, and the positioning performance of PPP-AR is analyzed and evaluated after OSB product correction. In terms of OSB product quality, the data availability (DA) of GPS satellite is greater than 94%, that of Galileo satellite is less than 56%, and the standard deviations (STD) of GPS and Galileo satellite are 0.053 and 0.075, 0.031 and 0.044 respectively. After correction by OSB products, the percentage of wide lane (WL) residuals of GPS and Galileo systems exceeds 90% and 83% within 0.25 cycle, and the percentage of narrow lane (NL) residuals of the two systems within 0.25 cycle is 83% and 81% respectively. As far as the positioning performance of PPP-AR is concerned, the positioning errors of GPS+Galileo dynamic PPP-AR in E, N and U directions are 1.45 cm, 1.51 cm and 4.16cm, respectively, and the ambiguity fixing rate is about 97%. Compared with PPP, the convergence time of PPP-AR corrected by OSB products can be shortened by more than 59%. However, due to the lack of phase deviation, there is a phenomenon of re-convergence in the positioning process. In this paper, Grey model is used to predict OSB data, which has certain reliability and significantly improves the situation of re-convergence.
How to cite: Huang, G., Yang, N., and Wang, L.: Performance analysis of undifferenced and uncombined PPP based on CNES OSB products, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9469, https://doi.org/10.5194/egusphere-egu25-9469, 2025.
This research involved an analysis aimed at determining the accuracy of results derived from the Trimble RTX web-based post-processing service for Multi-GNSS solutions. To achieve this, nine stations situated on the Eurasian plate were selected from the MGEX network set up by the IGS. A GNSS dataset from 2022 was processed using Trimble RTX. The data from these GNSS stations were analyzed as three satellite combinations: GPS-only, GPS-GLONASS, and GPS-GLONASS-Galileo.
Initially, a 3D transformation was applied to investigate statistically significant differences among the 24-hour processing results for the three combinations. Upon confirming that the differences in coordinates were statistically insignificant, the GNSS data was divided into two 12-hour datasets and three 8-hour datasets, which were then processed using Trimble RTX. The results from the 24-hour analysis were accepted as accurate for all three satellite combinations, and the differences between the 12-hour and 8-hour processing results were examined. The results indicated that, while the differences in coordinate components were insignificant, the use of all three satellite combination datasets contributed to both the Cartesian coordinate components and the standard deviation values.
How to cite: Oz Demir, D.: Statistical Analysis of Trimble RTX Service Processing Results, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9510, https://doi.org/10.5194/egusphere-egu25-9510, 2025.
This study examines the stability and temperature variations of SAPOS reference stations across Lower Saxony and neighboring federal states over a four-year period (2017–2020). SAPOS, the Satellite Positioning Service of the German National Survey, provides high-precision geodetic
reference points essential for applications such as surveying, navigation, and geographic information systems (GIS). Data from 43 SAPOS stations in Lower Saxony, ten SAPOS stations in adjacent regions, and 54 German Weather Service (DWD) stations were analysed using custom programs in Python
and MATLAB. The findings demonstrate the high SAPOS availability and station quality, though systematic effects were identified in the cleaned time series of topocentric coordinates for certain stations. These effects relate to multipath sensitivity, assessed using the Multipath Indicator (MPI),
which reflects signal reflection interference, confirming the high quality of SAPOS stations. The study corrected these effects via drift and offset adjustments and outlier removal. The analysis investigated five categories of deviations, revealing recurring patterns influenced by station type and installation characteristics. Notably, unilateral solar exposure and temperature fluctuations at the Braunschweig station caused deviations of up to 5 mm in the north and east components of topocentric coordinates.
How to cite: Zhu, Y., Schön, S., and Jahn, C. H.: Analysis of Stability and Temperature Variations in SAPOS Reference Stations in Lower Saxonyand Adjacent Regions between 2017 and 2020, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-21876, https://doi.org/10.5194/egusphere-egu25-21876, 2025.
The high latitudes are widely recognized as the most disturbed region of the ionosphere. The reason for that is the shape of the geomagnetic field and, related to this, the precipitation of energetic particles originating from the solar wind. The consequence of the strong plasma variation in the polar and auroral ionosphere is the deterioration of GNSS signal amplitude and phase, which may lead to losses of phase lock and cycle slips. The latter impact results in challenging scenarios for GNSS precise positioning based on phase data, but it may also be used to indicate the high-latitude ionosphere conditions. Since there is a correlation between GNSS signals scintillation and cycle slips, the analysis of the second parameter may support the climatological investigations for this area. Such an assumption allows us to use conventional GNSS data from permanent networks (of 1-30 s sampling rate), significantly extending the spatiotemporal distribution of measurements. Nevertheless, the adoption of cycle-slips number as a parameter describing ionospheric activity has to be preceded by cross-evaluation of its behaviour for different receivers and signals. This step is crucial, considering the increasing number of GNSS constellations and signals.
Motivated by such developments, we investigated the occurrence of cycle slips in GNSS phase data recorded by stations located at northern high latitudes. The basis for the analysis was multi-GNSS observations (GPS, GLONASS, Galileo, BDS) collected by permanent IGS/EPN stations. As a test period, we selected two major geomagnetic storms in 2024, which took place in May and October. The analysis confirms significant differences between the number of cycle slips for a particular system and signal. The discrepancies are also observed for collocated stations equipped with different receivers. The results indicate a need for unifying multi-GNSS cycle-slip numbers for climatological ionospheric studies.
How to cite: Sieradzki, R. and Paziewski, J.: The cycle-slips occurrence at high-latitude GNSS stations during geomagnetic storms – inter-receiver and inter-signal comparison, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-12253, https://doi.org/10.5194/egusphere-egu25-12253, 2025.
Recently, we have observed remarkable progress in algorithms aimed at precise point positioning (PPP) based on uncombined GNSS observations, also with an integer ambiguity resolution. Despite the high potential of such a model, its performance still depends on several factors, among which is the a priori information on slant total electron content (STEC), which is crucial. The ionospheric corrections may be obtained by converting VTEC from global ionosphere maps (GIM) using the selected ionospheric mapping function (MF). Thus, the accuracy of such STECs depends on the uncertainties introduced by both GIMs and MFs. Considering the latter, the most common approach is using a single-layer model (SLM) with a zenith angle as a parameter. However, it may be less effective for regions with strong TEC gradients that depend on azimuth. Improving such areas seems feasible with the support of ionosphere models and multi-layered mapping functions.
In this study, we evaluate the new multi-layered mapping functions. The new functions were developed, taking the Neustrelitz TEC Model as a basis. In this case, the ionosphere comprises numerous thin shells, and the ratio of aggregated slant and vertical TEC values provides the modeled mapping factors. Such derived MFs were validated based on PPP positioning performance. Also, an agreement analysis using the geometry-free linear combination was performed to assess the MFs in the GNSS observation domain. The preliminary tests involved GNSS data from several globally distributed stations, corresponding to different daily patterns of the ionosphere. The analysis provides the statistics for the low solar activity period (year 2019). According to the results, we can report a slight benefit from applying the multi-layered mapping function for PPP performance compared to the standard SLM approach. The advancement is the most noticeable for the positioning initialization period and, therefore, is reflected in the convergence time. The analysis performed with the geometry-free linear combination is consistent with PPP results, and it highlights the highest potential of the multi-layered mapping function for the equatorial region.
How to cite: Wielgosz, P., Sieradzki, R., Paziewski, J., Hoque, M., Frauenberger, O., Dhital, N., Nykiel, G., Milanowska, B., and Orus Perez, R.: Applicability of multi-layered mapping function to STEC/VTEC conversion – validation in PPP positioning and GNSS observation domains, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18016, https://doi.org/10.5194/egusphere-egu25-18016, 2025.
The tropospheric effect is considered as one of the most significant sources of error limiting GNSS positioning accuracy. In addition, atmospheric mass loading, which is seasonally variable, can also affect the repeatability of daily GNSS positions to a minor level. Therefore, the correct modelling of tropospheric and atmospheric loading effects is crucial to achieve the suitable accuracy, especially in high-accuracy GNSS applications. The aim of this work is to study the impact of tropospheric modelling and atmospheric mass loading on the repeatability of daily GNSS solutions. The research methodology is based on the analysis of GNSS data obtained from the IGS network, incorporating multiple processing scenarios including different mapping functions, elevation masks, and atmospheric mass loading. The analysis studies data from contrasting geographical locations (mid-latitude and polar regions), and accounts for seasonal variations by analysing measurements taken during both summer and winter periods, enabling a comprehensive assessment of how these various factors influence GNSS data processing outcomes, especially the daily position repeatabilities. The obtained results show that the efficiency of the mapping functions varies from one region to another. Furthermore, the consideration of atmospheric mass loading affects the performance of the mapping functions.
How to cite: Dekkiche, H., Namaoui, H., and Bouaoula, W.: Impact of tropospheric and atmospheric loading models on the repeatability of GNSS solutions, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-17541, https://doi.org/10.5194/egusphere-egu25-17541, 2025.
Seismic monitoring depends on accurately identifying P-wave and S-wave arrivals, which are critical for earthquake localization and Earthquake Early Warning (EEW). In EEW networks, a Global Navigation Satellite System (GNSS)-driven geodetic component enhances lead-time estimation and ground-shaking assessment, particularly for large earthquakes (Mw > 6.0). Advancing S-wave detection algorithms is essential to providing fast and reliable warnings to communities.
This study presents a sliding-window-based algorithm designed to detect the first time of arrival (ToA) of S-waves in high-rate (<1 Hz) GNSS instantaneous velocity time series without frequency-domain pre-filtering. The algorithm employs a three-phase process: (1) preprocessing, (2) statistical analysis and hypothesis testing for extracting ground-shaking disturbances, and (3) S-wave picking. It is implemented in an open-source Python-based toolbox, which also provides auxiliary seismic data, including ground-shaking duration, component-wise Peak Ground Velocity (PGV), and waveform energy.
The algorithm’s performance was evaluated using data from the 2016 Mw 6.2 Norcia and 2023 Mw 7.7 Kahramanmaraş-Gaziantep earthquakes. Results showed root mean square errors (RMSE) of 1.8 seconds and 3.8 seconds, respectively, when compared to ground-truth S-wave arrivals derived from P-wave readings on seismic waveforms recorded within 5 km of the GNSS sensors using the auxiliary Pphase-Picker software. The P-wave readings were extrapolated to GNSS sensor locations assuming equal P-wave velocities and a P-to-S-wave velocity ratio of 1.5.
Severe ground-shaking durations of up to 80 and 250 seconds, along with short S-P times of 3-5 seconds for the town of Norcia and the city of Gaziantep, highlight the severity of these events. This study demonstrates the new algorithm’s potential to enhance GNSS-based S-wave detection.
How to cite: Lapadat, A. M., Pierzchala, H., Kudłacik, I., Cai, Y., Aponte, O., Nastase, E. I., and Lackowski, M.: Automated S-Wave Arrival Timing in GNSS Instantaneous Velocity Data Without Frequency-Domain Pre-Filtering, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15685, https://doi.org/10.5194/egusphere-egu25-15685, 2025.
The southwest Pacific Region regularly produces tsunamis triggered by strong earthquakes of magnitude up to M8.1 associated to its complex tectonics and subduction processes. According to the NOAA/NCEI database, these tsunamis represent about one quarter of the tsunamis recorded worldwide. Some of them have been catastrophic for coastal populations in terms of the number of dead and injured and destructions of infrastructures or agriculture land. For example, the 2007 Solomon Islands & the 2009 Samoa tsunamis killed 50 and 192 people, respectively and did hundreds of millions of US dollars in damage. The present study focuses on the Solomon Islands which has suffered from several recent destructive tsunamis, including the tsunami in 2007, and a doublet tsunami in 2016. Only a few tide gauges and 2 Australian DART captured the tsunami signal, demonstrating the need for more densely spaced observations and direct measurements from the ocean, in order to improve the warning procedures, reducing the alert timing. One way to increase this observing capacity is to fill the geodetic observation gap in the ocean using a network of cargo-ships equipped with GNSS systems tracking anomalous variations of the sea-level. These measurements can potentially detect tsunamis of different origins. To complete the few available studies focusing on the Solomon Islands tsunamis, the project aims (i) to model the 2007 and 2016 tsunamis using the records/observations on land or close to the shore (e.g., seismic network, land-based GNSS and tide-gauges data), (ii) to compare their source and impact on population and infrastructure, (iii) to analyze what a constantly moving cargo-ship GNSS network might experience in terms of tsunami travel time and tsunami predicted amplitudes, and (iv) to determine how useful such a cargo-ship GNSS network would be to increase our ability to detect and respond to these hazards through local early warning. By exploring the relationship between tsunami sources, travel times and amplitudes using ships’ locations, the study seeks to determine the ability of a defined regional ship network to function as a low-cost method to improve the detection of tsunamis, and to improve effective warnings and hazard mitigation for coastal areas and the exposed communities in the region.
How to cite: Thomas, B. E. O., Roger, J., and Foster, J.: Evaluation of the ability of a cargo-ship GNSS network to detect tsunamis in the Solomon Islands region, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-13055, https://doi.org/10.5194/egusphere-egu25-13055, 2025.
This study addresses the scientific question of the applicability of low-cost antennas to the most precise GNSS applications. First of all, we inspect the implications of the availability and quality of low-cost antenna PCC models for precise positioning. From this point of view, we analyze the selected performance indicators of multi-constellation positioning with the representative set of low-cost mass-market GNSS receiver antennas. The processing strategy was based on the relative positioning model, considered the most reliable and precise one. To isolate the antenna-related errors from atmospheric propagation ones, we conducted an experiment based on an ultra-short baseline. As the main indications of low-cost antenna performance, we considered distance and height residuals, defined as the difference between benchmarks and the retrieved from GNSS measurements. We found that the low-cost antenna's PCV effect may significantly affect the final results. On the other hand, the results obtained using certain configurations of low-cost antennas were characterized by only slightly higher standard deviations and discrepancies with respect to benchmark values than those obtained with surveying or geodetic equipment. We identify several sets of low-cost antennas where distance residuals do not exceed 4 mm and height residuals do not exceed 6 mm, which shows the low-cost antenna performance comparable to those achieved using high-grade antennas. On this basis, we conclude that selected low-cost antennas can meet the requirements of high-precision surveying applications.
How to cite: Dawidowicz, K., Paziewski, J., Krzan, G., and Stępniak, K.: On the applicability of low-cost GNSS antennas to precise surveying applications, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18548, https://doi.org/10.5194/egusphere-egu25-18548, 2025.
To meet the demanding requirements in terms of accuracy and availability, GPS has introduced the signals on L5 that are compatible to Galileo E5a signals. The L5 signal was designed to mitigate the multipath and poor performance in harsh environments such as indoor, forests, and areas affected by jamming. As the L2 signal will become obsolete in the future, action must be taken to take advantage of the modern signal type which is currently broadcast by 19 out of GPS satellites. This is particularly important for some future LEO satellites (e.g. EPS-SG) which will rely exclusively on L1/L5. CODE (Center for Orbit Determination in Europe) is building up a prototype processing chain to generate L1/L5-based clock and bias products in addition to the classic L1/L2-based processing chain. First results regarding analysis product consistency are presented.
How to cite: Kalarus, M., Schaer, S., Dach, R., Arnold, D., and Jaeggi, A.: Towards new CODE analysis products based on GPS L1/L5 signals, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-17355, https://doi.org/10.5194/egusphere-egu25-17355, 2025.
Global navigation satellite systems (GNSS) are used for various applications in the Earth and atmospheric sciences, navigation, surveying and mapping, as well as in early warning systems for geo-hazards. Solutions are often required to not only be of high accuracy, integrity, and continuity, but also to be available in real-time with a delay of only a few seconds. A prerequisite for real-time precise point positioning (PPP) are precise satellite orbit and clock products. While satellite orbits can be predicted with high precision, at least for a few hours, the satellite clocks have to be estimated using real-time GNSS data from a global network of reference stations and distributed via real-time data streams to the user. GFZ is operating a real-time GNSS analysis center, which is contributing to the Real-Time Service (RTS) of the International GNSS Service (IGS). In this contribution, we introduce the new GFZ in-house real-time GNSS network analysis software that is currently being developed and provide an initial assessment of the generated products.
In the first development stage that is presented in this contribution, the generated products contain satellite orbits and satellite clocks referring to the ionosphere-free code observations. The orbits are taken from the predicted part of the operational GFZ IGS ultra-rapid GPS, GLONASS, and Galileo solution, which are updated every three hours. The associated satellite clocks are estimated every five seconds using a recursive least-squares estimator from globally recorded real-time dual-frequency code and phase observations, together with receiver clock parameters, tropospheric zenith delay parameters, inter-system biases, and carrier-phase ambiguities.
Important aspects are the data cleaning to obtain high-quality results and an efficient implementation of the estimation filter to satisfy the delay requirements of the products – less than five seconds for the IGS. For the data cleaning and cycle-slip detection, the concept of single-receiver, single-channel integrity is used, in which the uniformly most powerful invariant test statistics are evaluated separately for each satellite-receiver link using its code and phase observations of two consecutive epochs. For the estimation filter, a sequential Kalman filter implementation using the standard covariance form is used. ‘Sequential’ refers to the strategy that the scalar observations of the same epoch are processed sequentially one at a time, leading to a more efficient operation of the filter compared to the case that the entire vector of measurements is processed at once. With this strategy, the processing time per epoch is around two seconds.
An initial evaluation of this real-time satellite orbit and clock product will be presented by means of a direct comparison to post-processed multi-GNSS reference products and a comparison of PPP analyses using in addition also broadcast navigation data and real-time products of other analysis centers.
How to cite: Brack, A., He, S., Du, S., and Wickert, J.: Real-time GNSS for geosciences: Initial assessment of new data products from GFZ, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10805, https://doi.org/10.5194/egusphere-egu25-10805, 2025.
After Google’s release of Android Nougat (Android 7) in 2016, raw GNSS observations of Android smartphones have been freely accessible to the GNSS research community. Using smartphone raw GNSS measurements, numerous theories and practical methods were developed to achieve high precision in positioning, navigation, timing, and GNSS remote sensing. However, due to the chipset and built-in antenna quality, smartphone observations have more powerful noises compared to the geodetic grade GNSS receivers. Besides, frequent interruptions and cycle slips are present in smartphone observations. Therefore, it is difficult to achieve high positioning accuracy with smartphones, since it requires more sophisticated data processing methods. Smartphone stochastic modeling can be included in these methods since the variation of observation noise follows behaviors that are difficult to represent as a function of satellite elevation angle, while carrier-to-noise ratio (C/N0) representation provides a more suitable weighting scheme e.g., for smartphone Precise Point Positioning (PPP).
In addition to the current developments, analyzing the time-correlation behavior of smartphone observation noise can help to develop resilient algorithms for positioning, such as the detection of cycle slips, outliers, and adaptive filtering methods. In this contribution, we present noise analysis of smartphone raw GNSS measurements from different perspectives, namely stand-alone, double-differenced, and based on PPP residuals. To eliminate systematic effects such as the multipath effect from smartphone observations, we use a Kalman Filter algorithm and we compare it with Least Squares Harmonic Estimation (LS-HE). To investigate the time-correlation property of filtered observations, we use autocorrelation and Allan Deviation (AD) methods. Results showed that even if the strong periodicities of the multipath effect are filtered, there are residual multipath effects that remain in smartphone observations and residuals. Furthermore, AD analysis showed that smartphone observations/residuals contain white noise and time-correlated noise that exhibits similar characteristics to a Gauss–Markov process. Using these insights, our study discusses the influence of the weighting scheme and time-correlated errors on smartphone PPP and recently developed adaptive filtering techniques with the goal of improving PPP performance. We aim to provide a foundation for further advancements in modeling and mitigating multipath and time-correlated smartphone observation noises.
How to cite: Gul, C. and Warnant, R.: Stand-alone, double differenced, and residual-based noise analysis of smartphone raw GNSS observations, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-8500, https://doi.org/10.5194/egusphere-egu25-8500, 2025.
GNSS campaigns are still in use today especially for the monitoring of natural hazards such as landslides and local subsidence. Studying the velocity uncertainty of GNSS campaign deformation monitoring is a challenge among scientists cause the velocity error cannot always be characterized as pure white noise. We test the velocity uncertainty of GNSS campaign measurements referring to the mathematical theory developed to find the velocity uncertainty of GNSS continuous coordinate time series. GPS coordinate time series have been downloaded from the archive of NASA JPL. The time series have been decimated to annual synthetic GNSS campaigns because researchers usually can handle GNSS campaigns once every year in three or more consecutive days. Using the continuous GNSS coordinate campaigns we estimated the spectral indices for the 30 IGS stations spread across the globe. Then using these spectral indices and the formulation given in Zhang et al.1997, Mao et al. 1999, Dixon et al. 2000, and Williams 2003 we have developed a practical methodology to estimate noise amplitudes and velocity errors for the data of synthetically derived annual GNSS campaigns. The methodology avoids large matrix computations and consumes only a little PC memory. The velocity error derived using the above-mentioned approach has been cross validated by the velocity error derived from the sample of annual GPS campaign time series constituted employing the continuous GPS time series. 10-12 synthetically derived independent GPS annual campaign time series were formed from the continuous data of each of the thirty stations we used from the IGS network. Then the velocity error has been computed as the inter-quartile range of the velocities derived from those of the annually sampled time series. The inter-quartile range values are comparable with the velocity errors computed using the methodology described in this study. The significancy of the differences were also tested referring to Wilcoxon's Signed Rank hypothesis testing. The method has been found to be promising for the velocity error estimation of GNSS campaign measurements.
How to cite: Sanli, D. U., Ercoban, M., Aras, M. C., and Uysal, E.: A practical methodology to scale velocity uncertainties derived from GNSS campaign time series, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9699, https://doi.org/10.5194/egusphere-egu25-9699, 2025.
Global Satellite Navigation System (GNSS) has been widely used in our daily life, due to its high-precision positioning ability. However, in urban environments, GNSS signals are prone to obstructions from tall buildings, leading to Non-Line-of-Sight (NLOS) errors and a significant decline in positioning accuracy. Machine learning (ML) techniques for NLOS detection has emerged as a significant research hotspot, thanks to its advantages, such as requiring no hardware modifications, achieving high accuracy, and offering practical applicability, etc. However, the existing research on ML-based NLOS detection usually relies on single models, which are prone to becoming trapped in local optima during the optimization process. To overcome this limitation, we propose a GNSS NLOS detection method based on the Stacking Ensemble Learning (SEL) model. Initially, the fisheye camera is utilized to generate NLOS labels, and five GNSS signal features are extracted: elevation angle, carrier-to-noise ratio (C/N₀), measurement residual, C/N₀ rate of change, and pseudorange standard deviation. Subsequently, the SEL model is designed with a two-layer structure. The first layer consists of basic ML classification models, including Convolutional Neural Network (CNN), Gradient Boosting Decision Tree (GBDT), Random Forest (RF), and Support Vector Machine (SVM). The second layer employs Logistic Regression (LR) as the meta-learning model to integrate the outputs from the first layer. Finally, the trained SEL model processes the five GNSS signal features in real time for detecting smartphone GNSS NLOS signals, and incorporates a weighted model for SPP positioning. Several smartphone-based vehicle experiments were conducted in different urban areas of Wuhan, China, to validate the effectiveness of the proposed method. Experimental results demonstrate that the SEL method achieves GNSS NLOS detection accuracies exceeding 90%, with detection performance improvements ranging from 15.6% to 32.7%, compared with the single ML methods such as CNN, GBDT, RF, and SVM. Furthermore, the SEL method enhances 3D positioning accuracy, with improvements ranging from 26.7% to 39.6%. Particularly, in dense urban canyon areas, the vertical positioning accuracy is improved by up to 73.1%, effectively mitigating the impact of NLOS signals. This method requires no additional improvements to low-cost receiver hardware, thus offers potential for widespread application across various GNSS terminals, and provides new ideas for navigation and positioning in smart cities.
How to cite: liu, L., li, Z., and jiang, W.: An Enhanced Method for NLOS Signal Detection in Urban Environments based on Stacking Ensemble Learning for Smartphone Positioning, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-5389, https://doi.org/10.5194/egusphere-egu25-5389, 2025.
Posters virtual: Thu, 1 May, 14:00–15:45 | vPoster spot 1
EGU25-9320 | ECS | Posters virtual | VPS23
Signature of mantle anelasticity detected by GPS ocean tide loading observationsThu, 01 May, 14:00–15:45 (CEST) | vP1.16
Anelasticity is a type of rheology intermediate between elasticity and viscosity, responsible for rock’s transient creep behaviour. Whether to consider anelasticity in geodynamic processes operating outside the seismic frequency band which likely involve transient mantle creep is still under debate. Here, we focus on the geodynamic process of ocean tide loading (OTL), namely the deformational response of the solid Earth to the periodic ocean water-mass redistributions caused by astronomical tides. By analysing high-precision Global Positioning System (GPS) data from over 250 sites in western Europe and numerical OTL values from advanced three-dimensional Earth models, we unambiguously demonstrate anelastic OTL displacements in both the horizontal and vertical directions. This finding establishes the need to consider anelasticity in geodynamic processes operating at sub-seismic timescales such as OTL, post-seismic movement, and glacial isostatic adjustment (GIA) due to rapid ice melting. Consequently, to construct a uniform viscoelastic law for modelling Earth deformations across multiple timescales anelasticity must be incorporated. Our best-fitting anelastic models reveal the shear modulus in Earth’s upper mantle to be weaker at semi-diurnal tidal frequencies by up to 20% compared to the Preliminary Reference Earth Model (PREM) specified at 1 Hz, and constrain the time dependence of this weakening.
How to cite: Huang, P., Penna, N. T., Clarke, P. J., Klemann, V., Martinec, Z., and Tanaka, Y.: Signature of mantle anelasticity detected by GPS ocean tide loading observations , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9320, https://doi.org/10.5194/egusphere-egu25-9320, 2025.
EGU25-12972 | ECS | Posters virtual | VPS23
Advancements in Navigation Technology and Robustness Against GNSS Interference: A Comparative Analysis of CRPAThu, 01 May, 14:00–15:45 (CEST) | vP1.17
The progressive development of navigation technology has significantly improved real-time positioning accuracy, addressing the needs of modern applications. GNSS (Global Navigation Satellite System) is the primary system used for precise positioning across various platforms. However, GNSS is susceptible to errors, particularly interference, which degrades signal quality and compromises accuracy. Auxiliary systems such as INS, gyroscopes, and map-matching algorithms enhance reliability during interference but depend on GNSS for initialization. Signal detection algorithms, often employing CRPA (Controlled Reception Pattern Antennas) and advanced computational techniques, are essential for mitigating the impact of interferences and ensuring reliable navigation. This study compares the performance of two CRPA systems with different GNSS modules and algorithms, subjected to spoofing-jamming interference during experiments. The first CRPA, integrated with the u-blox ZED-F9P module, supports GPS, BeiDou, and Galileo satellites, employing an adaptive notch filter and pulse blanking. The second CRPA, featuring the Unicore UM980 module, supports GPS, BeiDou, and GLONASS satellites, utilizing a space-time algorithm alongside the JamShield adaptive mechanism for interference mitigation. In this study, real-time measurements were conducted on a car-mounted device platform under normal operating conditions. The platform was tested stationary for 5 minutes, followed by 15-minute intervals at speeds of 60 km/h. During each interval, 5 minutes of jamming and 5 minutes of spoofing were applied, with independent spoofing signals introduced. Jamming signals reached up to 50 dB-Hz, and spoofing signals were applied at levels up to 32 dB-Hz using a specialized interference device. During constant-speed travel, the second CRPA tracked 28 satellites with an HDOP of 0.5, while the first CRPA tracked 23 satellites with an HDOP of 0.75. Under jamming conditions, The second antenna maintained consistent satellite visibility, whereas the first experienced a pronounced decline in the number of observable satellites. Similarly, spoofing had no adverse effect on the second antenna, but the first suffered reduced satellite counts and positional accuracy. Additionally, the first antenna consistently underestimated the vehicle’s speed by approximately 5 km/h and exhibited a speed fluctuation of 0.5 m/s under interference conditions.
How to cite: Karlitepe, F., Sezen, S., Velibasa, B. E., and Kabalci, A.: Advancements in Navigation Technology and Robustness Against GNSS Interference: A Comparative Analysis of CRPA , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-12972, https://doi.org/10.5194/egusphere-egu25-12972, 2025.
