Volume 19, Issue 4

Global Navigation Satellite System (GNSS) products, including satellite orbit and clock corrections, ionospheric and tropospheric delay models, and multi-frequency data, are fundamental to modern geodesy and numerous scientific and industrial applications. The exploitation of these products facilitates the achievement of precise positioning, navigation, and timing (PNT) across a diverse range of fields, including transportation, geodesy, agriculture, and disaster management. Nevertheless, numerous challenges remain, including signal degradation due to multipath effects, atmospheric interference, and vulnerabilities to jamming and spoofing. Recent developments seek to address these limitations and enhance the utility of GNSS products. International collaboration, spearheaded by organizations such as the International GNSS Service (IGS), is crucial for standardizing and distributing GNSS products, facilitating global accessibility and addressing challenges such as climate monitoring and disaster resilience. This review emphasizes the indispensable role of GNSS products in advancing science and industry, highlights persistent challenges, and explores innovative solutions that promise to enhance their accuracy, resilience, and accessibility for addressing global needs.

Static relative Global Navigation Satellite Systems (GNSS) positioning is commonly used to achieve mm-level positioning uncertainty. However, few studies have examined the impact of baseline length to the positioning uncertainty. This study assesses 1,500 baselines across the five consecutive observation days and two plate motion inclusion options (15,000 baseline processing), to obtain the relationship between the baseline length and the positioning uncertainty. These baselines connect 25 International GNSS Stations (IGS) stations with the 60 Indonesia Continuously Operating Reference Stations (InaCORS) stations, continuous GNSS network in Indonesia. The 24-h GNSS data is processed using Bernese 5.2 to obtain daily coordinates solution in International Terrestrial Reference Frame 2014 (ITRF2014) with the uncertainty in the east/north/up component. Results show that longer baselines produce higher uncertainties, following an exponential trend. The east component has the lowest uncertainty due to the predominant east baseline azimuths. Baseline azimuths and plate motion considerations slightly influence uncertainty, but baseline length plays a much more significant role. Excluding plate motion noticeably increase uncertainty for baselines over 5,000 km. Specific uncertainty levels can be inferred from the exponential function, such as the baselines under 3,800 km are required for horizontal uncertainties under 3 mm. This exponential function also serves as a basis for selecting the constrained station in the GNSS data processing with the static relative GNSS positioning method.

This paper presents a comparative study on the calibration of magnetometer sensors, focusing on three methods: the least square method, the ellipsoid fitting method, and a proposed sequential method. The effectiveness of the first two methods is investigated, and their results are compared with the outcomes achieved through the application of the sequential method. Practical data is utilized to demonstrate the advantages of the proposed method. Through this research, insights are provided into the performance and limitations of the least square and ellipsoid fitting methods, while highlighting the superior capabilities of the sequential method. The results show that the sequential method inherits the capabilities of both method and leads to a more reliable calibration.

This study explores the potential of GNSS-levelling to complement geometric levelling in the state levelling network, particularly outside the main lines. The Polish state levelling network plans to reduce the number of points from 40,000 to 16,000 during upcoming updates. GNSS-levelling is considered a cost-effective solution for filling gaps in the network, especially in rural areas. The experiment, commissioned by the Polish Head Office of Geodesy and Cartography, applied Polish geometric levelling accuracy criteria and tested them against GNSS-levelling. The goal was to develop a technique that an average surveying company could apply. The results showed that the initial hypothesis of GNSS-levelling’s suitability was not fully supported, primarily due to inconsistent vector repeatability. Accuracy could be improved by increasing the number of observation sessions or using specialized GNSS software while still maintaining cost-effectiveness. The experiment was conducted in an area where the state quasi-geoid model fits the levelling network with an accuracy of ±1 cm. Furthermore, the single vector solution (SVS) outperformed the each-to-each vector strategy (NET) in aligning with this network. Although challenges remain, GNSS-levelling demonstrates the potential and after refinement of techniques requirements, it is possible to obtain the main goal.

The Palu region has attracted attention due to significant seismic activity, including a destructive earthquake in 2018. This study aims to investigate postseismic deformation following the 2018 Palu-Donggala earthquake using the Interferometric Synthetic Aperture Radar (InSAR) technique. We utilized Global Navigation Satellite System (GNSS) data to obtain the viscoelastic mechanism decay time. Therefore, we subtracted the viscoelastic relaxation signal to obtain spatiotemporal afterslip distribution inferred from the 2.5D InSAR observation based on the Steepest Descent Method (SDM). Our results suggest the viscoelastic mechanism is indispensable, with an optimal decay time of about 2 years after the earthquake. Based on the chi-square statistical test, the spatiotemporal afterslip model can explain the observation with good qualification. We found anomalies indicating non-decreasing slip, which is likely due to several factors, such as the presence of Slow Slip Events (SSE). These findings provide valuable insights regarding the potential for future earthquakes and have significant implications for disaster risk assessment in the Palu region and its surroundings.

This study evaluates the performance of two Precise Point Positioning (PPP) software solutions, GAPS and GAMP, for estimating Vertical Total Electron Content (VTEC). Their outputs were compared against the International Reference Ionosphere (IRI) models, the Center for Orbit Determination in Europe (CODE) solutions, SWARM satellite data, and COSMIC-1 observations. The results demonstrate that GAPS achieves superior accuracy and reliability after initialization, with VTEC estimates closely aligning with CODE, IRI, COSMIC-1, and SWARM data. In contrast, GAMP, while exhibiting faster convergence, showed greater variability and a tendency to underestimate VTEC, especially under dynamic ionospheric conditions. Statistical analyses revealed that GAPS produced lower Root Mean Square (RMS) errors across stations, with values below 20 Total Electron Content Units (TECU) when compared to CODE, IRI and between 5 and 25 TECU when validated against COSMIC-1 and SWARM data. Conversely, GAMP’s RMS values reached up to 65 TECU, indicating lower precision. GAPS also showed smaller average and absolute differences, confirming its ability to capture localized ionospheric variations more effectively than GAMP and IRI models. A t -test analysis indicated no statistically significant differences between GAPS and CODE, IRI, SWARM, or COSMIC-1 for most stations, demonstrating the robustness of GAPS in representing ionospheric behavior. GAMP, however, often exhibited significant differences in VTEC estimates relative to these references. These findings demonstrate GAPS’s superior performance in ionospheric studies and VTEC estimation, underscoring the importance of choosing suitable PPP solutions and prepossessing for high-precision GNSS and atmospheric research.

In recent years, the usage of point cloud data for various mapping and other civil engineering tasks has become increasingly popular. The detailed acquisition of the environment forms a great advantage compared to point-wise methods using e.g. total station measurements. The major drawback is, that the uncertainty analysis of the measured points and accordingly the derived parameters is not straightforward. A variance propagation of the observations would not lead to plausible results, since the stochastic model is unknown in most of the cases. In this work, we present an empirical way to determine uncertainty information of the point cloud data captured by a mobile mapping system (MMS) related to height differences by using mainly the road surface, where the system drives on. Height differences between objects are often considered in the context of monitoring of land subsidence and engineering structures or mapping tasks. For the evaluation, height differences between points are analyzed, which differ in three major aspects from each other: the distances between the height observations, the environmental conditions, and the locations in the measurement volume of the system. Repeated measurements of the road surface and artificial targets are used to evaluate the precision of the height differences. Using reference values enables an analysis of the full uncertainty information. The results from two data sets show, that the environmental conditions severely influence the GNSS quality and consequently the precision of height differences decreases. Due to positive correlations between neighboring points, which are caused by the trajectory information, the height difference uncertainty increases concerning the traveled distance between the points. Because of remaining calibration errors, the location of the objects within the measurement volume of the profile laser scanner also influences the uncertainty of the height values and thereby also of height differences.

This research investigates the application of gap and flush measurements between structural car components as part of the quality assurance process in Mercedes-Benz production. The measuring tool, attached to a lightweight robot (LBR), is mounted on a driverless platform Kuka-Motion-Platform (KMP). The study collects measurement data during three critical production phases: car body construction, car varnishing, and body assembly. Throughout the entire production process, observing gap and flush values ensures the fulfilment of both functional and customer requirements. At the assembly line, two measurement approaches are used: Full Automatic Gap-Measuring Installations (SMA): These installations automatically measure gap and flush values. If errors are detected during measurement, the affected car bodies are diverted from the production lane. Hand-Held Instruments: Adjacent to the production line, two employees perform rework and repeat quality measurements to meet the required quality targets. Once corrections are successfully executed, the cars re-enter the production line. The study explores gap measurement using mobile measurement units (SME) in human-robot interaction (HRC). These mobile units, currently fixed in position, offer enhanced automation and flexibility within the production process. Future plans involve replacing the static SMA with systems like SME. Additionally, the research aims to develop a scalable and autonomous measuring system. Toward this goal, two main components from the SME the measurement devices and the LBR, are mounted on the KMP. The empirical determination of measurement device variance at the desired gap is achieved through propagation of uncertainty. In summary, this study contributes to the advancement of quality assurance practices in Mercedes-Benz car production by leveraging innovative measurement techniques and automation.

Rapid variations in the amplitude and phase of signals travelling through the ionosphere of the Earth are known as ionospheric scintillations. This study presents the results of amplitude and phase scintillation characteristics at different L-band signal frequencies of six satellite constellations. The scintillation data was acquired using Septentrio’s PolaRx5S Ionospheric GNSS scintillation monitoring receiver located at a low latitude station. Samples of S 4 and σ φ data above standard threshold values with a 30° elevation mask for 293 days of the year 2023 are considered for analysis. Three aspects of scintillations are studied: i) statistics of their occurrences at different frequencies for all constellations ii) the correlation between amplitude and phase scintillation parameters for different frequencies iii) the temporal and spatial distributions of amplitude and phase scintillation at selected intensity levels. The results shows that about 70 % of total scintillation activity occurred during 20:30 to 22:59 LT. Further it is found that the signals coming in northern direction followed by southern direction are most affected compared to other directions indicating more ionospheric irregularities in those directions. This information is useful for identifying the least scintillation affected signals for position fixing.

The Precise Point Positioning (PPP) technique has been utilized to process the Global Navigation Satellite Systems (GNSS) annual datasets at 24 stations in the Nile Delta region, Egypt from 2012 to 2024. The present study aims to present recent estimates of horizontal crustal deformation, vertical land movements, and the analysis of the International Terrestrial Reference Frame (ITRF) coordinate conversion between the two utilized ITRF frames in Egypt, namely ITRF2020 (epoch 2024) and ITRF2008 (epoch 2012). Based on the accomplished findings, it has been found that the land subsidence in the Nile Delta region ranges between −3.9 mm/year and 2.3 mm/year with an average of −1.5 ± 1.9 mm/year. Regarding the horizontal crustal movements, it is recognized that such crustal deformations vary between 25.8 mm/year to 27.6 mm/year with an average equals 27.0 ± 1.0 mm/year. In addition, the average direction of that deformation equals 38.6° ± 2.1°. Such results agree normally with those of other studies concerning the regional movements of the Nubia tectonic plate. The attained simple mathematical model describing the relationship between ITRF2024 and ITRF2008 frames shows that the average Cartesian displacement vector equals −0.312 m ± 0.026 m, 0.153 m ± 0.010 m, and 0.152 m ± 0.020 m in the X , Y , and Z directions respectively. Additionally, the velocities are −24 ± 2 mm/year, 12 ± 1 mm/year, and 12 ± 2 mm/year respectively.

The continuous and accurate determination of positions, velocities, and time in Global Navigation Satellite Systems (GNSS) fundamentally relies on the precise knowledge of satellite orbits and clock information. These critical components, commonly referred to as orbit and clock files, serve as the backbone of GNSS systems such as GPS, GLONASS, Galileo, and others. They play an essential role in enabling high-accuracy positioning services for a wide range of applications, including navigation, mapping, scientific research, and time synchronization. A clear understanding of the principles and functionality of these orbit and clock files is paramount for comprehending the intricate mechanisms that underpin GNSS systems and their profound impact on positioning accuracy. This study provides a comprehensive exploration of GNSS systems with a particular focus on accuracy enhancement. The research primarily aims to elucidate the pivotal role played by a diverse array of organizations in supplying accurate and reliable orbit and clock files. By examining the multifaceted contributions and effects of these entities, the investigation unveils the complex processes through which GNSS accuracy is elevated to unprecedented levels. The findings underscore the indispensable contributions of these organizations in advancing the precision and reliability of GNSS technologies, thereby highlighting their critical importance in supporting the ever-growing demands of global positioning and timing applications.

The paper presents smartphone GPS positioning results, using phase observations on the L1 frequency. In this research, we used one Huawei P30 Pro mobile phone, one Samsung S22 Ultra, and one geodetic receiver (Javad Triumph-1) acting as the reference receiver. Smartphones were placed on an aluminum base at an equal distance of 0.34 m from this receiver. Such a close distance was used to achieve identical observation conditions. The analysis was carried out from static GPS positioning, using the Modified Ambiguity Function Approach (MAFA) method. The short baselines were used during the tests. For the first part of the test, 5-min static sessions were performed for both smartphones. For post-processing kinematic (PPK), 1, 3, 5, and 10-s solutions achieved decimeter-level accuracy, while 30 and 60-s solutions provided centimeter-level accuracy for N and E on both smartphones. The results obtained from both smartphones are very promising. The authors proved that the MAFA method can be used for precise mobile phone positioning for short baselines.

Low satellite signal quality in urban areas is caused by multipath interference resulting from the abundance of various obstacles that limit satellite visibility performance, leading to poor satellite geometry and an increase in dilution of precision (DOP). The chance of encountering multipath significantly increases when receiving reflected signals from non-line-of-sight (NLOS) satellites, causing large positioning errors in pseudorange measurements. Enhanced identification of the multipath error source can improve positioning accuracy. This study first detected and then minimized multipath effects in pseudorange measurements using two unsupervised learning techniques – K-means and Fuzzy c-means (FCM) – which executed clustering across diverse multipath conditions and different combinations of GNSS, handled unlabeled quantitative data, and defined a certain number of clusters. Results indicated comparable performances of the K-means and FCM algorithms, with horizontal positioning accuracy improved by up to 35 % and vertical accuracy enhanced by up to 27 %.

The disturbance in ionospheric conditions caused by geomagnetic storms leads to problems with the ground, satellite communication, and navigation technology. The Ionospheric perturbations affect the accomplishment of the Global Navigation Satellite System (GNSS), namely accuracy, continuity, availability, and integrity. During the ionosphere’s disturbance level, the Precision and safety of GNSS applications are essential to obtain data about space weather conditions. Along different GNSS satellite receiver paths, GNSS receivers are particularly vulnerable to expeditious changes in Total Electron Content (TEC) and critical spatial variations. The ionospheric indices, namely the Gradient Ionosphere Index (GIX), Rate of TEC Index (ROTI), and the Sudden Ionospheric Disturbance Index (SIDX), are employed for monitoring ionospheric conditions. The ionospheric disturbances can be assessed using GIX and SIDX without prior data. These indices have been modeled and validated based on GNSS observations provided by the Indian region. This research work examines the effects of the ionosphere on the St. Patrick’s Day geomagnetic storm (17th March 2015) by inspecting TEC variations from March 14 to 19, 2015, using spatial and temporal indices for GNSS stations at Trivandrum, Hyderabad, Mumbai, Kolkata, Bhopal, Delhi positioned in the Indian subcontinent. In low-latitude regions, the highest GIX, ROTI, and more negative SIDX values started recording from 1,200 h UT to 1,500 h UT on 17th March 2015. On 17th March 2015, during the storm’s main phase, the selected stations showed GIX values ranging from 47.2 to 103.3 m TECU/km. On Recovery Day 19th March 2015, GIX readings range from 38.1 to 60 m TECU/km, this research plays a part in understanding ionospheric gradients in the equatorial and low latitudes, where it is applicable for improving Ground Based Augmentation Systems (GBAS) and GPS-aided GEO Augmented Navigation (GAGAN) effective for aircraft landing.

The kinematic precise point positioning (KPPP) is one of the best techniques aiming for zero-difference precise positioning. Recent studies have shown a growing use of KPPP in several kinematic platform-based applications for precision approach. This study therefore aims to explore the impact of the ionospheric plasma density perturbations on the KPPP, which bear significant effect over the global equatorial and low latitude belt. With a unique data set of simultaneous observations from a reference station and a close-by scintillation monitoring station located within Hyderabad in India, a study of impact of post-midnight scintillations on KPPP is performed. A 4-year duration around peak of the solar cycle 24 between 2013 and 2016 is considered for KPPP analysis by GipsyX software using continuous observations. The daily ENU (east, north, up) residuals are obtained by subtracting the monthly mean precise position from the daily 30-s sampled KPPP estimates. Then the nighttime ENU residuals (between 18:00 and 06:00 Indian standard time, IST) are segregated into pre-midnight (18:00 to 00:00 IST) and post-midnight (00:00 to 06:00 IST) intervals for all the nights. Owing to a different nature of post-midnight irregularities over the equatorial and low latitudes, the results are obtained for post-midnight KPPP. The amplitude scintillation index S4 is obtained for the corresponding nights for all the days and simultaneous records are used to obtain a few case studies of very high ENU residuals reaching up to 20 m in some cases. Also, the statistical analysis of the ENU shows a decreasing trend in the amplitude of ENU perturbations from midnight to morning hours, wherein, maximum perturbations are observed from 00:00 to 01:00 local time. Conclusions are presented in comparison with the previous literature, and it is found that this could possibly be the first report of the post-midnight impact of the ionospheric scintillation on the KPPP over Indian region.