Global Navigation Satellite System System Research Articles

Virtual Validation of In-Flight GNSS Signal Reception during Jamming for Aeronautics Applications

Accurate navigation is a crucial asset for safe aviation operation. The GNSS (Global Navigation Satellite System) is set to play an always more important role in aviation but needs to cope with the risk of interference, possibly causing signal disruption and loss of navigation capability. It is crucial, therefore, to evaluate the impact of interference events on the GNSS system on board an aircraft, in order to plan countermeasures. This is currently obtained through expensive and time-consuming flight measurement campaigns. This paper shows on the other hand, a method developed to create a virtual digital twin, capable of reconstructing the entire flight scenario (including flight dynamics, actual antenna, and impact of installation on aircraft) and predicting the signal and interference reception at airborne level, with clear benefits in terms of reproducibility and easiness. Through simulations that incorporate jamming scenarios or any other interference scenarios, the effectiveness of the aircraft’s satellite navigation capability in the real environment can be evaluated, providing valuable insights for informed decision-making and system enhancement. By extension, the method shown can provide the ability to predict real-life outcomes even without the need for actual flight, enabling the analysis of different antenna-aircraft configurations in a specific interference scenario.

Reservoir landslide monitoring and mechanism analysis based on UAV photogrammetry and sub-pixel offset tracking: a case study of Wulipo landslide

Introduction: Reservoir landslides undergo large deformations during the early stages of impoundment and maintain long-term persistent deformations during the operational period of the reservoir. The management of reservoir landslides mostly focuses on the early identification, risk assessment during the large deformations, and long-sequence monitoring during long-term persistent deformations, which requires sufficient continuity and integrity of the landslide monitoring data.Methods: Taking the Wulipo (WLP) landslide in Baihetan Reservoir as example, this paper proposes a reservoir landslide monitoring method that integrates field survey, unmanned aerial vehicle (UAV) photogrammetry and global navigation satellite system (GNSS) monitoring, which can effectively eliminate the practical monitoring gaps between multiple monitoring methods and improve the continuity and completeness of monitoring data.Results and discussion: First, this study determined the initiation time of the landslide through the field investigation and collected five period of UAV data to analyze the overall displacement vector of the WLP landslide using sub-pixel offset tracking (SPOT). On the basis of the above data, we compensated for the missing data in GNSS system due to the practical monitoring vacancies by combining the field survey and the landslide-water level relationship. Based on these monitoring data, this paper points out that the WLP landslide is a buoyancy-driven landslide, and whether or not accelerated deformation will occur is related to the maximum reservoir water level. Finally, this study analyzed and discussed the applicability of UAV photogrammetry for reservoir landslide monitoring in the absence of ground control points (GCPs), and concluded that this method can be quickly and flexibly applied to the stage of large deformation of reservoir landslides.

A compliance assessment of GNSS station networks in Serbia

Since the early 21st century, Global Positioning System (GPS) technology has dominated geodetic reference networks. Almost all countries established a permanent Global Navigation Satellite System (GNSS) station network to augment all available GNSS systems. By the end of 2005, Serbia completed the Active Geodetic Reference Network as a particular project of Serbia's Republic Geodetic Authority (RGA). Besides RGA, two private companies, Vekom and Geotaur, have established permanent station networks. This paper assesses the compliance of all the three networks, and network results are evaluated against the spatial distance determined by classical geodetic methods. When all available GNSS constellations are utilized, NAVSTAR, GLONASS, BEIDOU, and GALILEO, in the processing procedure, the established networks in Serbia align within a margin of about 3 mm across all coordinate axes. The results obtained within the research indicate that by using GNSS networks, it is possible to provide the coordinates of the points for the establishment of the national spatial reference system of Serbia, the reference system in almost all engineering fields, reference systems for the maintenance works of the real estate cadastre, and it is also possible to provide coordinates of points that can be used to define local, national, and world reference heights surfaces.

Intelligent Environment-Adaptive GNSS/INS Integrated Positioning with Factor Graph Optimization

Global navigation satellite systems (GNSSs) applied to intelligent transport systems in urban areas suffer from multipath and non-line-of-sight (NLOS) effects due to the signal reflections from high-rise buildings, which seriously degrade the accuracy and reliability of vehicles in real-time applications. Accordingly, the integration between GNSS and inertial navigation systems (INSs) could be utilized to improve positioning performance. However, the fixed GNSS solution uncertainty of the conventional integration method cannot determine the fluctuating GNSS reliability in fast-changing urban environments. This weakness becomes solvable using a deep learning model for sensing the ambient environment intelligently, and it can be further mitigated using factor graph optimization (FGO), which is capable of generating robust solutions based on historical data. This paper mainly develops the adaptive GNSS/INS loosely coupled system on FGO, along with the fixed-gain Kalman filter (KF) and adaptive KF (AKF) being taken as comparisons. The adaptation is aided by a convolutional neural network (CNN), and the feasibility is verified using data from different grades of receivers. Compared with the integration using fixed-gain KF, the proposed adaptive FGO (AFGO) maintains the 100% positioning availability and reduces the overall 2D positioning error by up to 70% in the aspects of both root mean square error (RMSE) and standard deviation (STD).

A multimodal fusion positioning method with adaptive driving behavior for intelligent vehicles

Due to the difficulty of Global Navigation Satellite System (GNSS) in urban canyon environments, GNSS and inertial navigation system (INS) fusion positioning is widely used in the field of intelligent driving. In actual positioning, INS usually uses the vehicle physical model as a constraint to calculate inertial measurement unit (IMU) data to supplement the vehicle position and attitude as GNSS positioning information. However, the existing algorithms usually use a fixed physical model. When the vehicle’s driving behavior changes, such as lane-changing, acceleration, deceleration, etc., the fixed model cannot provide long-term constraints on cumulative errors, resulting in a decrease in fusion positioning accuracy and stability. Therefore, this paper proposes a multimodal fusion positioning method with adaptive driving behavior for intelligent vehicles. First, to adapt to multimodal driving behavior, a multimodal assisted positioning physical model with adaptive driving behavior (MAPM) is established, which expresses different physical models probabilistically based on driving behavior and historical data. Secondly, high-precision estimation of vehicle positioning parameters is achieved based on model probability and interactive multi-model (IMM). Finally, effective fusion of MAPM/GNSS/INS positioning information is achieved under the federated Kalman filtering framework. The simulation results show that compared to traditional GNSS/INS fusion positioning, the proposed method can effectively improve positioning accuracy and stability, especially in driving conditions with changes in driving behavior.

Responses of the Nigerian low-latitude ionosphere to geomagnetic storms of the ascending and maximum phases of solar cycle 24

This study investigates the responses of the Nigerian ionosphere to thirteen geomagnetic storms that occurred during the ascending and maximum phases of the solar cycle 24. The Total Electron Content (TEC) data obtained from the Nigerian Global Navigation Satellite System (GNSS) network (NIGNET) were used.The ionosphere over Nigeria recorded marked diurnal TEC variations around 1100–1700 LT, with the most significant variations between 1400 and 1600 LT time period, and minimum variation at 0600 LT. Another cogent piece of information from this study is that the values of TEC and ionospheric irregularities at all the five GNSS stations under investigation consistently matched one another. The implication of this is that the values of TEC and irregularities, at both quiet time and storm time, at any location in Nigeria could be used as the representative values at any other locations in the country, particularly in areas where there are no GNSS systems. The equinoctial maxima and June solstice minima effects were clearly observed in our data. Furthermore, ionospheric irregularities occurrences also followed semiannual patterns with two peaks in April and October, and the least occurrences in June, and generally localized around 2000–0100 LT. At daytime during geomagnetic storms in the equatorial/low-latitude regions, Prompt Penetration Electric Field (PPEF) intensified forward plasma fountain effect, while at nighttime, the reversed plasma fountain effect returns plasma backward to cause the Equatorial Ionization Anomaly (EIA) crests to contract, or totally coalesce the EIA structure to form a single strip of plasma density around the equator.

A Multi-Depth Deflectometer/Global Navigation Satellite System Method for Measuring Concrete Slab Track Deformation

This study introduces a Multi-Depth Deflectometer (MDD) combined with a Global Navigation Satellite System (GNSS) which was developed for measuring the deformation of railway slab track layers. We newly designed the MDD with the addition of laser sensor modules for increasing precision in which the MDD head is fixed at the top of the track slab. The MDD/GNSS system can measure the relative deflection between each track layer as well as the total deflection at the top of the track slab, which makes it possible to evade the fixed condition problem of classical MDD. The new MDD/GNSS system was installed at the transition zone between a tunnel entrance and its embankment, which experienced high settlement levels prior to repair. The system was used to monitor whether the repaired concrete track foundation with pressurized cement grouting was stabilized effectively and what track layer position was most unstable so that it had the most influence. The GNSS system was designed and built for computing net settlement at each track layer even when the MDD could not be fixed firmly at the end point, which is a major drawback of classical MDD. The results obtained from MDD and GNSS measurements indicated significant potential in aiding railway track settlement measurements.

LIDAR SLAM-AIDED VEHICULAR NAVIGATION SYSTEM FOR GNSS-DENIED ENVIRONMENTS

Abstract. Typically, in situations where Global Navigation Satellite System (GNSS) signals are unavailable, navigation systems rely on integrating GNSS and inertial navigation system (INS) data. While such integration can provide accurate positioning during short GNSS signal outages, it cannot sustain prolonged GNSS outages. The reason for this is that the system's performance depends solely on the INS and can result in significant errors over time. To address this issue, additional onboard sensors are necessary. This study proposes a navigation system that integrates INS and LiDAR simultaneous localization and mapping (SLAM) using an extended Kalman filter (EKF). The system was tested using the raw KITTI dataset in various outdoor driving scenarios without GNSS signals. It is shown that the proposed system significantly outperformed the INS-only system, with an average RMSE improvement of around 93% and 58% in the horizontal and the up directions, respectively.

Enhanced GNSS Reliability on High-Dynamic Platforms: A Comparative Study of Multi-Frequency, Multi-Constellation Signals in Jamming Environments

The global navigation satellite system (GNSS) signals are vulnerable to disruption sources, such as signal jamming. This, in turn, can cause severe degradation or discontinuities of the GNSS-based position, navigation, and timing services. The availability of multi-frequency signals from multi-constellation GNSS systems, such as Galileo and GLONASS, along with the modernization of GPS with multi-frequency signals, has the potential to increase the immunity of GNSS-based navigation systems to signal jamming. Despite various studies completed on the utilization of multi-frequency and multi-constellation global navigation satellite system (GNSS) signals to resist receiver jamming, there is still an urge to further investigate this concern under different circumstances. This paper presents an experimental evaluation of the advantages of the employment of multi-frequency multi-constellation GNSS signals for better GNSS receivers’ performance during signal jamming situations for high-dynamic platforms such as aircraft/drones. Additionally, the study examines the effects of both simulated and real jamming signals on all possible combinations of the GPS, Galileo, and GLONASS signal frequencies and constellations. Two airplane trajectory routes were built, and their corresponding RF signals were generated using the Spirent and Orolia GNSS signal simulators. The results indicated that the GPS multi-frequency-based solution maintains reliable positioning performance to some extent under low jamming scenarios. However, the combination of GPS, Galileo, and GLONASS signals proved its ability to provide a continuous and accurate positioning solution during both low and high jamming scenarios.

Sky-view images aided NLOS detection and suppression for tightly coupled GNSS/INS system in urban canyon areas

Although the global navigation satellite system (GNSS) and inertial navigation system (INS) integration framework has many advantages compared to the standalone GNSS and INS systems, its accuracy can be severely degraded in urban canyon areas, due to non-line-of-sight (NLOS) signals. Detection and suppression of NLOS signals are the key to improving the location accuracy of urban areas. Therefore, this paper proposes a method for NLOS detection using the improved region growing algorithm on sky-view images captured by a fish-eye camera. After obtaining NLOS detection results, this paper constructs a weighted model with an adaptive scale factor to suppress the influence of NLOS signals. Experimental results show that the proposed method can effectively improve the performance of NLOS detection and suppression. On this basis, a tightly coupled GNSS/INS integration system based on an extended Kalman filter is developed and tested on the vehicle equipment. Results show that the proposed method outperforms the traditional GNSS single point positioning (SPP) and tightly coupled GNSS SPP/INS integration on positioning accuracy. The root mean square error can be reduced by 33.7% and 24.6% in the north and east directions respectively. It indicates that the tightly coupled GNSS SPP/INS integration aided by the fish-eye camera has certain research value and potential on positioning in urban canyon areas.

Enhancing accuracy of information processing in onboard subsystems of UAVs

The object of research is the onboard subsystems of Unmanned Aerial Vehicles (UAVs). The research is aimed at analyzing UAVs, specifically the integration and enhancement of satellite-based positioning systems, including Global Navigation Satellite Systems (GNSS) and Inertial Navigation Systems (INS). The problem concerns traditional satellite-based positioning services, especially those relying solely on medium earth orbit (MEO) satellites, which are insufficient for specific requirements. The study aims to address the limitations of these systems on onboard subsystems of UAVs, especially in challenging environments laden with jammers and interference, and to provide a more accurate, robust, and continuous positioning solution. The research proposes a «multilayer system of systems» approach that integrates signals from various sources, including low Earth orbit (LEO) satellites, ground-based positioning, navigation, and timing (PNT) systems, and user-centric sensors. The combined approach, termed LeGNSS/INS, leverages the strengths of each component, providing redundancy and enhanced accuracy. The system's performance was evaluated using pseudo-real output data, demonstrating its ability to generate quasi-real dynamic trajectories for UAV flight. The error analysis showed that the proposed method consistently outperforms traditional GNSS systems, especially in challenging environments. The enhanced performance of the LeGNSS/INS system can be attributed to integrating multiple satellite systems with INS and applying optimal filtering techniques. The research also employed mathematical modeling to represent the dependencies and interactions when combining data from different sources, such as GPS, LEO, and INS. The Kalman filter is a mechanism to fuse data from multiple sources optimally. The insights from this study apply to various sectors, including aviation, maritime navigation, autonomous drones, and defense. The enhanced positioning accuracy can significantly improve safety, navigation precision, and operational efficiency. However, the study assumes idealized conditions for satellite signal reception, which might not always be accurate in real-world scenarios. Challenges, such as the martial law conditions in Ukraine affecting data collection and potential satellite signal restrictions, were also highlighted. Further research can delve into the impact of more complex environmental factors and the integration of additional satellite systems or sensors to enhance accuracy further.

Preliminary Assessment of BDS Radio Occultation Retrieval Quality and Coverage Using FY-3E GNOS II Measurements

The FengYun-3E Global Navigation Satellite System (GNSS) occultation sounder II (FY-3E GNOS II) was launched on 5 July 2021. For the first time, based on the new GNOS II sensor, this mission realizes radio occultation (RO) and reflectometry observations using the navigation signals from the third-generation BeiDou System (BDS-3), and it is hence important to assess and analyze the BDS-3 remote sensing performances relative to other systems. Here, we assessed FY-3E GNOS II RO atmospheric retrievals by inter-comparing with corresponding data from the NCEP FNL global atmospheric analysis and FY-3D GNOS mission. The GNOS RO data quality and consistency of the different FY-3 meteorological satellites, i.e., FY-3D and FY-3E, as well as different GNSS systems (GPS, BDS-2, BDS-3) were analyzed. We find that the FY-3E GNOS II RO data exhibit better quality than FY-3D GNOS, particularly in the number, penetration height toward surface, and global coverage by BDS RO profiles, due to the integration of BDS-2 and BDS-3. Additionally, comparing with co-located NCEP FNL analysis profiles, the mean difference (and standard deviation) of the FY-3E GNOS II RO atmospheric refractivity profile retrievals is found to be smaller than 0.2% (and 1%), in the upper troposphere and lower stratosphere, from 5 to 30 km, and remains consistent at this accuracy and precision level with the FY-3D GNOS RO data. These features provide clear evidence for a high utility of the new GNOS II RO data for weather and climate research and applications.

Performance analysis of frequency-mixed PPP-RTK using low-cost GNSS chipset with different antenna configurations

Low-cost Global Navigation Satellite System (GNSS) devices offer a cost-effective alternative to traditional GNSS systems, making GNSS technology accessible to a wider range of applications. Nevertheless, low-cost GNSS devices often face the challenges in effectively capturing and tracking satellite signals, which leads to losing the observations at certain frequencies. Moreover, the observation peculiarities of low-cost devices are in contradistinction to those of traditional geodetic GNSS receivers. In this contribution, a low-cost PPP-RTK model that considers the unique characteristics of different types of measurements is developed and its performance is fully evaluated with u-blox F9P receivers equipped with three distinctive antenna configurations: vertical dipole, microstrip patch, and helix antennas. Several static and kinematic experiments in different scenarios are conducted to verify the effectiveness of the proposed method. The results indicate that the mixed-frequency PPP-RTK model outperforms the traditional dual-frequency one with higher positioning accuracy and fixing percentage. Among the three low-cost antennas tested, the vertical dipole antenna demonstrates the best performance under static conditions and shows a comparable performance as geodetic antennas with a positioning accuracy of 0.02 m, 0.01 m and 0.07 m in the east, north, and up components, respectively. Under low-speed kinematic scenarios, the helix antenna outperforms the other two with a positioning accuracy of (0.07 m, 0.07 m, 0.34 m). Furthermore, the helix antenna is also proved to be the best choice for vehicle navigation with an ambiguity fixing rate of over 95% and a positioning accuracy of (0.13 m, 0.14 m, 0.36 m).

Machine learning approach for prediction of total electron content and classification of ionospheric scintillations over Visakhapatnam region

Ionospheric scintillations, which are due to ionospheric plasma density anomalies, negatively impact trans-ionospheric signals and the positioning accuracy of the global navigation satellite system (GNSS). One of the crucial variables for comprehending space weather conditions is the total electron content (TEC) of the ionosphere. It is vital to predict the ionospheric TEC before making efforts to enhance the GNSS system. In this article, the long short-term memory machine learning approach for TEC prediction is presented, based on which the ionospheric phase scintillations are identified and classified using popular classifiers: support vector machines and decision trees. In this article, the comparative analysis of these classifiers is presented using the standard performance metrics: accuracy, recall, precision, and F1 score.

Kinematic Precise Point Positioning Performance-Based Cost-Effective Robot Localization System

The use of high-precision positioning systems in modern navigation applications is crucial since location data is one of the most important pieces of information in Industry 4.0, especially for robots operating outdoors. In the modernization process of global navigation satellite system (GNSS) positioning, precise point positioning (PPP) has demonstrated its effectiveness in comparison to traditional differential positioning methods over the past thirty years. However, various challenges hinder the integration of PPP techniques into Internet of Things (IoT) systems for robot localization, with accuracy being a primary concern. This accuracy is impacted by factors such as satellite availability and signal disruptions in outdoor environments, resulting in less precise determination of satellite observations. Effectively addressing various GNSS errors is crucial when collecting PPP observations. The paper investigates the trade-off between kinematic PPP accuracy and cost effectiveness, through the examination of various influencing factors, including the choice of GNSS system (single or mixed), observation type (single or dual frequency), and satellite geometry. This research investigates kinematic PPP accuracy variation on a 10.4 km observed track based on different factors, using the GNSS system (single or mixed), and observation type (single or dual frequency). It can be concluded that mixed (GPS/GLONASS) dual frequency offers a 3D position accuracy of 9 cm, while mixed single frequency offers a 3D position accuracy of 13 cm. In industry, the results enable manufacturers to select suitable robot localization solutions according to the outdoor working environment (number of available satellites), economical constraint (single or dual frequency), and 3D position accuracy.

GNSS-5G Hybrid Positioning Based on Joint Estimation of Multiple Signals in a Highly Dependable Spatio-Temporal Network

The Global Navigation Satellite System (GNSS) has been widely used in every area of our daily life to provide accurate Positioning, Navigation, and Timing (PNT) services. However, due to the multipatch effect and an obstructed view of the satellite, GNSS receivers are susceptible to large-ranging errors, which are particularly prevalent in urban areas where precise positioning is indispensable. The deployment of the high-spatial-density Fifth-Generation (5G) network makes it possible to provide a broad area with high-precision positioning service. Obviously, it promoting the deep integration of the GNSS system and the 5G mobile communication network and establishing a Highly Dependable Spatio-temporal Network (HDSN) have become an inevitable trend. The existing algorithm for the fusion of multiple signals has difficulty settling problems such as the fast fluctuation of available signal sources and the poor stability of multi-scale multi-type signal estimation in GNSS-5G hybrid networks. Here, we propose a Square Root Unscented Stable Filter (SRUSF) for GNSS and 5G joint positioning with a compact coupled filter group architecture in a highly dependable spatio-temporal network. A stabilized coefficient is added to guarantee positive covariance of the estimation error. The possibility of divergence of filtering results due to the variation in signal sources and the incomplete agreement between the system model and the actual situation are reduced. The simulation results show that the proposed SRUSF method substantially enhances the positioning accuracy and reliability compared with the other five joint estimation methods for multiple signals. This work will enable the terminal of mass users to provide timing and positioning services with unprecedented accuracy and dependability under the GNSS and 5 G-based spatio-temporal network’s architecture.

Adapting empirical solar radiation pressure model for BDS-3 medium Earth orbit satellites

For the precise orbit determination (POD) of global navigation satellite systems (GNSS) constellation, it is very difficult to precisely model the solar radiation pressure (SRP) force acting on GNSS satellites. For GPS satellites, the ECOM model developed by the Center for Orbit Determination in Europe has been utilized by most of International GNSS Service (IGS) analysis centers. However, it should be adapted and optimized to the characteristics of satellites of each GNSS system or even individual satellites. It was extended to the ECOM2 model for GLONASS satellites and then for Galileo satellites by employing a box–wing model. Since November 2020, the third generation of the BeiDou satellite system (BDS-3) has been in its full operation and there are about 200 globally distributed IGS ground stations tracking BDS-3 signals, which creates a great potential to evaluate and optimize its SRP modeling. From the POD processing carried out in this study, we found significant fluctuations of up to 20 cm in overlapping orbit differences for satellites over eclipses in the radial direction and of about 20 and 50 cm in the cross and along directions for ECOM2 and ECOM models. Then, based on numerical analyses we demonstrate that the fourth- and sixth-order sine terms in the Sun direction can significantly reduce the overlapping orbit differences of ECOM. Therefore, an adapted SRP model by adding the fourth- and sixth-order sine periodical terms in the Sun direction to the ECOM model is presented. The adapted model is then validated for BDS-3 POD and orbit prediction. Results show that fluctuations in the amplitude of overlapping estimated orbits using ECOM models are reduced from 20 to < 10 cm in the radial-track component and satellite laser ranging residuals are reduced to half by the adapted SRP model. For the predicted BDS-3 satellite orbits, the RMS values over deep eclipses can be improved from about 7, 14 and 26 cm to about 3, 5 and 12 cm, in the radial, cross and along directions, respectively, compared to the ECOM model.

Assessing the agreement between a global navigation satellite system and an optical-tracking system for measuring total, high-speed running, and sprint distances in official soccer matches.

This study aimed to compare the agreement of total distance (TD), high-speed running (HSR) distance, and sprint distance during 16 official soccer matches between a global navigation satellite system (GNSS) and an optical-tracking system. A total of 24 male soccer players, who are actively participating in the Polish Ekstraklasa professional league, were included in the analysis conducted during official competitions. The players were systematically monitored using Catapult GNSS (10-Hz, S7) and Tracab optical-tracking system (25-Hz, ChyronHego). TD, HSR distance, sprint distance, HSR count (HSRC), and sprint count (SC) were collected. The data were extracted in 5-min epochs. A statistical approach was employed to visually examine the relationship between the systems based on the same measure. Additionally, R2 was utilized as a metric to quantify the proportion of variance accounted for by a variable. To assess agreement, Bland-Altman plots were visually inspected. The data from both systems were compared using the estimates derived from the intraclass correlation (ICC) test and Pearson product-moment correlation. Finally, a paired t-test was employed to compare the measurements obtained from both systems. The interaction between Catapult and Tracab systems revealed an R2 of 0.717 for TD, 0.512 for HSR distance, 0.647 for sprint distance, 0.349 for HSRC, and 0.261 for SC. The ICC values for absolute agreement between the systems were excellent for TD (ICC = 0.974) and good for HSR distance (ICC = 0.766), sprint distance (ICC = 0.822). The ICC values were not good for HSRCs (ICC = 0.659) and SCs (ICC = 0.640). t-test revealed significant differences between Catapult and Tracab for TD (p < 0.001; d = -0.084), HSR distance (p < 0.001; d = -0.481), sprint distance (p < 0.001; d = -0.513), HSRC (p < 0.001; d = -0.558), and SC (p < 0.001; d = -0.334). Although both systems present acceptable agreement in TD, they may not be perfectly interchangeable, which sports scientists and coaches must consider when using them.

UAS-LC-GNSS: Precision Surveying with a Low-Cost GNSS System for Commercial Drones

INGV (National Institute of Geophysics and Volcanology, Italy) is one of the institutions that studies and monitors the geophysical phenomena (earthquakes, volcanic eruptions, landslides, etc.) that occur on Earth. During these events, it is essential to carry out a large, detailed and fast map of the affected areas.If we think of the difficulties encountered during the mapping of the fault sources for the 2016 earthquake in central Italy, we can understand how the UAS (Unmanned Aircraft System) can be a valid “low-cost” alternative to the traditional methods of surveys.These devices, thanks to precision instrumentation such as GNSS (Global Navigation Satellite Systems) receivers and IMU (Inertial Measurement Unit) control units, allow a detailed reconstruction of the investigated areas, especially for small-scale analysis applications. These aircraft are based on multiple technologies and show great investigative capabilities, therefore they must be considered as complete systems.Starting from these concepts, we have developed a low-cost RTK/PPK (Real Time Kinematic/Post Processing Kinematic) GNSS survey system on “commercial” UAVs (Unmanned Aerial Vehicles), i.e. professional drones that are not created to be modified.We have demonstrated how the integration of a GNSS RTK/PPK module on commercial UAVs makes the system efficient for the reconstruction of a highly detailed and precise DEM (Digital Elevation Model), without using GCP (Ground Control Point), allowing to make precision measurements in areas that are difficult to explore and investigate.

Multipath Impact on Multi-Frequency and Multi-Constellation Code Measurements from Brazilian GNSS Stations

Although Global Navigation Satellite Systems (GNSS) positioning can achieve high accuracy in line-of-sight conditions, multipath remains a dominant source of error. Multipath occurs when the reflected signals reach the receiver in addition to the direct ones. Different systems design can impact the multipath effect, such as the signal modulation and chipping rate. In the context of multifrequency and multi-constellation scenario that we are achieving with four operational global constellations, this paper compares the multipath impact in different signals of GPS, GLONASS, Galileo and BeiDou. For the experiment, one week of data from 35 Brazilian Network for Continuous Monitoring of the GNSS Systems (RBMC) stations in June 2021 was processed. The multipath index was estimated based on the code- inus-carrier combination. For the first frequency of each system, similar results were obtained for GPS, GLONASS and BeiDou (approximately 56 cm). The Galileo BOC/AltBOC modulation offers better resistance to multipath, with a multipath index of 37 cm for E1 and of 12 cm for E5. Considering all selected stations, the multipath index of GPS L1 varied from 38 cm to 61 cm.