Abstract With the rapid development of various software for processing data, it is essential to determine the most efficient and dependable use of existing processing software for Global Navigation Satellite System (GNSS) post-processing. This study compares different software packages used for post-processing GNSS measurements in a static mode. The research involved collecting data from dual-frequency GLONASS/GPS receivers at 15 IGS stations, recorded with a 30-second observation interval. The data sets were processed using industry-standard software packages, such as GNSS Solutions, Waypoint GrafNav, Magnet Office Tools, Leica Geo Office, Justin, and Trimble Business Center. All data sets were processed under standardized conditions, and positioning performance was evaluated using a PPP-derived reference solution. Statistical metrics, including mean error, standard deviation, and root mean square error, were calculated for horizontal and vertical components. The results confirm that Waypoint GrafNav and Magnet Office Tools provided better results for horizontal coordinate determination, while GNSS Solutions performed better in establishing point heights. This study underscores the importance of choosing the right software and processing methodology to attain an accuracy of centimeters when making multi-GNSS static measurements. Such insights have practical implications for engineers and surveyors in making informed decisions on the choice of post-processing software.
Modern marine gravity surveys are very costly and time-consuming. In the 1960s to 1980s, many marine gravity measurements were carried out in the southern and eastern Baltic Sea, mainly with the support of the research infrastructure of the Soviet Union. During the period of independence from the Soviet Union and transformation of the political system, much of these older data remain forgotten or not fully used. Now, it is scientifically and economically justified to reactivate these historical data so that they can supplement the modern surveys. This study presents the historical Polish marine gravity data, which were measured during four campaigns: Zaria, Jan Turlejski, Petrobaltic, and Ustka-Rozewie in 1971-1981 in the southern Baltic Sea. The datasets were transformed to modern geodetic and gravity reference frames, taking into account the available documentation. Next, a simple procedure was proposed for the determination of grid resolution, and the gridded 1 '& times;1 ' free-air and Bouguer anomalies were calculated for each survey. The resulting gridded anomalies were validated by three global geopotential models: EGM2008, EIGEN6c4, and GECO. Additionally, depths measured during the survey were validated using the ETOPO 2022 bathymetric model.
This paper proposes a novel framework for detecting and mitigating multipath interference in Global Navigation Satellite Systems (GNSS), a common issue caused by reflections of signal off surfaces such as buildings and the ground. To address this challenge, the study integrates Differential GNSS (DGNSS) techniques with advanced machine learning models, such as Support Vector Machine (SVM), Convolutional Neural Network (CNN), and Random Forest-to automatically detect and exclude satellites affected by multipath. The methodology involves synchronized GNSS data collection from a stationary base station and a mobile rover using high-precision u-blox ZED-F9P receivers with polarized antennas, DGNSS corrections via single and double differencing, and feature vector construction from both corrected and raw observation data. Signal quality labels ("Clean" or "Noise") are derived through skyplot analysis and environmental modeling. Three classification approaches are explored: direct classification using DGNSS-derived vectors (Approach 1), image-based classification (Approach 2), and classification using combined feature vectors (Approach 3). Experimental evaluation using 2,312 labeled samples shows that ensemble learning significantly outperforms single-model classifiers for multipath detection. Random Forest achieves the highest performance across all approaches, reaching up to 99.75% accuracy, while CNN outperforms traditional methods, reaching up to 86.77% accuracy in image-based classification in Approach 2. The findings demonstrate the effectiveness of the framework in identifying and excluding compromised satellite signals, which has the potential to enhance the accuracy of GNSS positioning, with potential for real-world application in complex urban environments.
The Indian Regional Navigation Satellite System (IRNSS), or NavIC, provides regional satellite positioning services across India and parts of Southeast Asia. In this study, we develop and evaluate a software-defined receiver (SDR) enhanced with deep learning techniques to acquire the IRNSS Standard Positioning Service (SPS) L5-band signal. The SDR architecture incorporates data-driven improvements in acquisition decision-making while retaining compatibility with the IRNSS signal structure as specified in the official ICD. Field experiments were conducted in Hanoi, Vietnam, a location situated at the fringe of NavIC's primary service area. Signal data were collected using a low-cost RF front-end connected to a rooftop-mounted antenna. Experimental results demonstrate that the proposed SDR is capable of reliably acquiring and tracking up to four IRNSS satellites under nominal conditions. The average C/N0 ranged from 30 to 42 dB-Hz, and successful position solutions were obtained with a horizontal accuracy of approximately 25 meters. Additionally, the deep learning-based acquisition module improved robustness in low-SNR scenarios. This work represents the first implementation of a learning-aided IRNSS receiver validated in Vietnam and offers insights into extending NavIC-based positioning services to broader Southeast Asian regions.
Variations in the Earth's rotation are intimately linked to geodynamical processes. Investigating secular change in the Earth's rotation can provide a profound understanding of the Earth system. Currently, continuous sequence of the Earth's variable rotation spans less than 400 years. Some researchers have employed historical records of ancient astronomical phenomena, particularly observations of solar and lunar eclipses, to study the Delta T value, which characterizes the secular change in the Earth's rotation. This study examines the corresponding Delta T value by combining total solar eclipse observations from Chinese historical documents on June 25, A.D. 1275.
NRLMSISE is an empirical model that allows us to predict temperatures and densities of the main atmospheric components. The model is widely used to evaluate atmospheric impacts on satellite orbits and laser beam refraction which come through the atmosphere, such as those used for Earth-satellite distance measurements. Model of the atmosphere is a valuable part of the Satellite Laser Ranging processing software like Kyiv Geodynamics (Juliette). Juliette is written in C++ and exploits the C++ clone of NRLMSISE written by the second author. The C++ version produces the same outputs as an official Fortran code.Accurate modeling of atmospheric influences on satellite motion requires performing numerous calculations along satellite orbits or laser beam paths, which are computationally intensive. By decreasing calculation time of NRLMSISE, we would not only save the modeling time but also give a prospect for a wider application of the model due to lowering computational resource demands.Our work demonstrates how the traditional NRLMSISE model can be effectively translated into a neural network. This conversion achieves significant performance gains on both CPU and GPU while maintaining acceptable accuracy when compared to the C++ implementation of NRLMSISE.We demonstrate the process of moving NRLMSISE to a neural network, the resulting accuracy, ease of running the trained model on CUDA-enabled GPUs, and the obtained boost of performance on both CPU and GPU.
Disturbances in the ionospheric plasma due to geomagnetic storms and thunderstorms recorded by the DEMETER and Swarm satellites are presented. Lightning and, in particular, transient luminous events (sprites, jets, elves and halos) are associated with the electromagnetic links and interactions between the atmosphere, ionosphere and magnetosphere and with intense thunderstorm activity. DEMETER has clearly shown that thunderstorms and sprites can affect the ionosphere even at its orbital altitude (680 km). Additional information on ionospheric disturbances comes from data collected by the Swarm satellites. The Swarm constellation consists of three identical satellites. Two of them operate in circular polar orbits with an initial altitude of 460 km, while the third satellite has a circular orbit but an altitude of 530 km. The orbits of the first two satellites are almost in the same plane, but the third satellite is almost perpendicular to the first two. The payload, which includes a vector field magnetometer, an absolute scalar magnetometer and an electric field instrument, will make it possible to study the effects of thunderstorms on the ionosphere. Registrations of ionospheric disturbances collected by DEMETER and Swarm during selected strong geomagnetic storms and thunderstorms over Poland and Central Africa are presented, and the similarities and differences are discussed.
The space plasma has relatively low energy but is dense in the low Earth orbit (LEO). In this study, we prepared various samples of anodic alloy surfaces with coating thicknesses of 20, 25, 35, and 45 mu m to identify the most suitable characteristics for space applications. Ground-based tests were conducted at the Laboratory of Lean Satellite Enterprises and In-Orbit Experiments at the Kyushu Institute of Technology. A radio frequency (RF) plasma source was used to generate a simulated LEO plasma using argon gas in a vacuum chamber. The plasma properties were measured with a Langmuir probe under different test conditions. A negatively biased voltage of -450 V was applied to the samples to study charging/discharging phenomena. The samples were exposed to Ar-plasma for 1-2 h. The physical properties and structural morphology of various alloy samples were analyzed before and after exposure to plasma. This analysis involved ultraviolet (UV)/visible (Vis)/ Near-Infrared (NIR) absorption spectra, Energy Dispersive X-ray (EDX) analysis, and surface roughness testing. The results showed that space plasma notably impacts the physical properties and morphology of the alloys. A coated thickness of around 25 mu m is considered more suitable for spacecraft surface structures due to its improved optical stability and resistance to plasma degradation, as indicated by the experimental results.
The advances in Machine Learning (ML) and computer technologies enabled to process satellite images using programming. Environmental applications that handle Remote Sensing (RS) data for spatial analysis use such an approach, for example, Python's library scikit-learn using algorithms on pattern identification, predictions or image classification. This paper presents an ML method of satellite image processing using Geographic Resources Analysis Support System (GRASS) Geographic Information System (GIS). The aim is to classify multispectral Landsat images using ML for identification of changes in salt pans of West Mauritania, Africa over the period 2014-2023. We define 10 classes of land cover categories and perform analysis of geological, lithological and landscape setting, and then introduce the principles, algorithms and processing of the ML methods of GRASS GIS. The following classification models were employed to implement image classification with training: Random Forest (RF), Decision Tree, Gradient Boosting and Support Vector Machine (SVM). The results were compared with clustering performed by k-means and maximum likelihood discriminant analysis. The cartographic visualisation and validation was implemented through accuracy analysis. Results for the best performing SVM model with seven-band input produced an overall accuracy of 76%, for the RF model - 73%, compared to 69% for Decision Tree Classifier - 69% and for Gradient Boosting Classifier - 67%. The SVM model embedded in GRASS GIS generates robust land cover maps with good accuracy from multispectral satellite images. The paper demonstrated an ML-based automated approach to satellite image processing, which links Artificial Intelligence (AI) with cartographic tasks.
The orbits of Global Navigation Satellite System (GLONASS) satellites are computed from the broadcast ephemerides using the fourth order of the Runge-Kutta integration method. Usually, the initial conditions used in the integration of the differential equation of satellite motion are the three positions and the three velocities of satellites at the initial time, and the results are the position and velocity at a given time; the luni-solar perturbation is supposed to be constant during the integration interval. The algorithm used is known in the documentation as the simplified algorithm; this algorithm was modified and replaced by the one called in this investigation as the simplified-modified algorithm, where the luni-solar accelerations were taken as variable terms and three linear functions modeling these luni-solar accelerations were added to the simplified algorithm. The ode45 MATLAB solver, based on the fourth and fifth orders of the Runge-Kutta method, was used to solve the differential equations describing the motion of GLONASS satellites in orbit. The data used in this study is the broadcast orbit files of 24 GLONASS satellites between March 1 and 21, 2024. The results obtained showed an improvement of 1.76 m and 0.0027 m/s in the positions and velocities of GLONASS satellites, respectively, when the simplified-modified algorithm was applied, that is, the three luni-solar accelerations were assumed as variable terms.
The copper belt of Anti-Atlas is recognized with several mineral occurrences of Cu, Zn, Mn, Ag, Au, and iron. We used ASTER and OLI in lithological and mineral detection and mapping. The lithological mapping was performed using principal components analysis (PCA), minimum noise fraction (MNF), and two classifiers: maximum likelihood (ML) and support vector machine (SVM). The hydrothermally altered zones were detected based on ASTER VNIR/SWIR bands by the integration of Ninomiya indices and constrained energy minimization (CEM) algorithm. In our study area, the enhanced band combinations of ASTER MNF1, PC4, and PC2 and OLI MNF1, PC5, and PC3 were applied for lithological discrimination. The OLI and ML classification shows the best lithological mapping accuracy with an overall accuracy of 91.74% and a 0.90 Kappa coefficient, followed by SVM with an overall accuracy of 88.82% and a 0.86 Kappa coefficient using the same sensor. The hydrothermal alteration mapping reveals alunite, chlorite, calcite, epidote, illite, kaolinite, montmorillonite, muscovite, and pyrophyllite minerals, principally in phyllic and argillic altered areas. The adopted methodology for lithological and mineralogical mapping can be used in other regions with similar criteria to the study area.
On the dwarf planet Ceres, there are bright spots known as faculae. Four types of faculae are distinguished: (a) floor faculae, (b) faculae on Ahuna Mons, (c) rim/wall faculae found on craters' rims or walls, and (d) ejecta faculae in the form of bright ejecta blankets. Our investigation on the interaction of the hypothesized subsurface originated jet of gas and the granular material indicated that floor faculae (a) could be a result of separation of fine bright component of regolith. Here, we consider the hypothesis that the ejecta faculae (d) may be the result of separation of grains due to explosive gas expansion during the formation of the impact crater. We consider the axisymmetric gas motion above the surface of Ceres. We transform our system of equations into a dimensionless form. Our numerical model indicates that the separation effect is strong enough to separate the grains (according to size, density, and other aerodynamics properties). In some cases, separation gives a monotonic, systematic effect: smaller particles are ejected farther than heavier particles. Generally, however, the distance over which the particles will be thrown depends in a rather complicated way on the parameters of the particles and the parameters of motion of the gas. This property fits the faculae of type (d). Because we used the dimensionless form of the equations, our results can be also applied to other celestial bodies where the regolith contains volatile substances. This paper is an extension of our investigations on the origin of faculae (a).
It is well known that the phase center of a Global Navigation Satellite System (GNSS) antenna is not a stable point. For any given GNSS antenna, the phase center will change with the direction of the incoming signal from a satellite, as well as the frequency. Ignoring these phase center variations (PCVs) in GNSS data processing can lead to notable errors, especially in vertical position component determination. To avoid the problem, antenna PCV together with the phase center offset (PCO) information are recommended to be used in GNSS observation processing. We currently distinguish between individual and type-mean phase center correction (PCC) models. These models describe the variations in the phase center of the antenna as a function of the elevation angle and azimuth. In general, the primary difference between individual and type-mean models lies in their specificity. Individual models are highly precise but are valid only for a particular antenna model, while the type-mean models are more general and can be applied to a broad range of antennas of the same type, but may suffer from a lower level of precision. This paper aims to analyze the comparability of PCV in surveying-grade GNSS antennas. For the analyses, we propose to use an originally designed bench with precisely defined relative positions of the seven antenna mounting points. Preliminary studies have been performed using GPS observations on L1 and L2 frequencies recorded by seven Topcon HIPER-VR antennas. The results proved that the comparability of PCV for this antenna is high. The position error did not exceed 3 mm. It could be assumed that the type-mean PCC model could describe PCV all antennas of this type with good accuracy.
Satellite altimetry provides high-accuracy geometrical measurements of sea level changes. We analyze altimetry time series representing sea surface height anomalies over the mean sea surface provided by the TOPEX/Poseidon, Jason-1, Jason-2, and Jason-3 satellite missions to estimate the annual rate of sea level rise. Then, we compare the results with satellite gravimetric data from GRACE and GRACE Follow-On missions and surface water temperature data, employing statistical analyses to examine the interrelationships and correlations between them. We carry out the main analyses for the period 2001-2021 with a division into 5-year periods for six different areas of the Baltic Sea. The altimetric results show that between 2001 and 2021, the water level of the Baltic Sea rose by 5.8 mm/year on average. About 72% of the changes detected by altimetry missions can be explained by satellite gravimetry from GRACE and GRACE Follow-On, which means that the mass component is responsible for most of the observed sea level change, whereas the remaining 28% can be greatly explained by thermal expansion due to the water temperature rise.
Since 2017, the Space Research Centre of the Polish Academy of Sciences in Warsaw, Poland, has measured and gathered over 35,000 hours of observations with the use of the LOw Frequency ARray (LOFAR) radio telescope. This paper outlines the Standard Data Product acquired from the LOFAR PL610 station located in Bor & oacute;wiec, Poland. Within this context, we detail the data products that are accessible, provide metadata descriptions for them, and include an example of the data under both quiet and disturbed ionospheric conditions.
In the course of satellite observations using satellite laser ranging (SLR), a key task is pointing the telescope with high precision. Positioning the steering system's mechanical parts with zero error is impossible. Accordingly, we must analyze and account for pointing errors by incorporating the telescope mounting errors themselves into the modeling error. Such models are far from trivial owing to the factors such as satellite azimuth, altitude, perhaps distance, or meteorological data.In this article, we explain how the data for the telescope pointing inaccuracy model (TIM) was collected and how a neural network was used to build a very precise TIM for the Golisiiv 1824 SLR station in Kyiv.We have focused our efforts on the suggested approach's positive aspects based on our experience of using it to find practical solutions. Our practical recommendations may also be interesting for anyone working with hardware, especially in analyzing their errors. The key proof of the effectiveness of the approach is the serious increase in the number of satellites successfully tracked, especially for "blind" paths, when the satellite is not visible to the observer through the telescope guide.
The standard recommended atmospheric gravity correction is based on the International Association of Geodesy (IAG) approach. This correction introduced into the results of gravimetric measurements reduces, in a simplified way, the influence of the actual atmospheric masses and the atmospheric masses contained inside a reference ellipsoid from the determined gravity anomalies or disturbances. Model of the actual atmosphere used in the IAG approach does not take into account topography as the lower boundary of the atmosphere, assuming that the atmosphere consists of spherical, constant density layers. In this study, we determined and analysed the components of atmospheric gravity correction for the area of Poland and its surroundings, considering topography as the lower limit of the atmosphere. In the calculations, we used algorithms typical for determining the topographic gravity reduction, assuming a model of atmospheric density based on the United States Standard Atmosphere 1976 model. The topography-bounded gravity atmospheric correction values determined were within the limits of 0.748-0.886 mGal and were different from standard, approximate atmospheric correction values in the range of 0.011 mGal for points at the sea level up to 0.105 mGal for points located at an altitude of approximately 2600 m.
Modeling the behavior and shape of space objects is widely used in modern astrophysical research methods. Such studies are often used to determine the shape and modeling of physical parameters of variable stars and asteroids. Therefore, based on the database of photometric observations of resident space objects (RSO) available in the Laboratory of Space Research of Uzhhorod National University, it was decided to find a means for modeling light curves to confirm the shape of objects and determine the parameters of their rotation by analogy with objects in deep space. We attempted to use Blender software to model the RSO synthetic light curves (LCs). While Blender has been a popular open-source software among animators and visual effects artists, in recent years, it has also become a tool for researchers: for example, it is used for visualizing astrophysical datasets and generating asteroid light curves. In the process of modeling, we used all the advantages of Blender software such as Python scripting and used GPU. We made synthetic LCs for two objects - TOPEX/Poseidon and COSMOS-2502. A 3D model for Topex/Poseidon was available on the NASA website, but after research of official datasheets, we figured out that the available 3D model requires corrections in the dimensions of the RSO body and solar panel. A 3D model of COSMOS-2502 was made according to available information from the internet. A manual modeling process was performed according to well-known RSO's self-rotation parameters. For example, we also show the results of LC modeling using the Markov chain Monte Carlo (MCMC) method. All synthetic LCs obtained in the research process are well correlated with real observed LCs.
Nowadays, space debris is one of the main subjects of discussion regarding satellites in Earth's orbit. Right now, there are about 26,000 orbiting satellites and only few of these satellites are operational. Recently, the Polish space sector has been strongly growing and delivering instruments working in space. The first part of this paper describes the several space instruments designed in the Space Research Centre Polish Academy of Science (SRC PAS). Instruments such as SWI, RPPWI, LPPWI, Ebox or Pre-boxes have been created for a mission to Jupiter named "JUICE". After fulfilling their scientific mission, these instruments can increase the amount of debris in space. This is one of the reasons for taking up the topic of space debris reduction and the use of technical solutions used in this mission for the proposed solution presented later. The second part of this paper describes the new methods related to space debris. The activities can be related to the space debris removal programmes. The paper describes two methods developed by Polish scientists used for removal of space debris. One of them is the new capture method and mechanism designed for it. The special mechanism is based on tubular boom application for opening the net, to capture the space debris. The main parts of the mechanism are mechanisms which have been used in the JUICE space mission. The paper describes the main idea for these new methods, and for the design part prepared the strength confirmation by structural analysis. The main function of the mechanism has been verified by simulations and tests performed in laboratories.
In situ resource utilization (ISRU) activities are receiving increasing attention, both from space agencies and among the international science and industrial community. Prominent examples of ongoing ISRU space programs are the NASA Artemis program and the Terrae Novae program run by the European Space Agency. In technical sciences, there are at least three groups of activities related to ISRU: prospecting bodies in the context of space missions, technological investigations related to surface infrastructure and operations, and conceptual analyses of future mining activities. The present paper belongs to the third group and brings new insights into a potential open pit mine operating on the Moon. There are several novel contributions: the definition of the objectives of the mine, based on economic indicators; a conceptual description of a pit architecture dedicated to excavating ilmenite-rich feedstock; and a qualitative and quantitative description of the chosen processes and the mine's topology. In the paper, there are also added links to other papers connected with ISRU activities.
