GNSS Performance Research Articles

Performance of Low-Cost GNSS in Structural Health Monitoring Studies: Shake Table Tests

Performance of Low-Cost GNSS in Structural Health Monitoring Studies: Shake Table Tests

Asymptotic Performance of GNSS Positioning Approaches under Cross-Correlation Effects

Asymptotic Performance of GNSS Positioning Approaches under Cross-Correlation Effects

Comparing Positioning Performance of LEO Mega-Constellations and GNSS in Urban Canyons

Comparing Positioning Performance of LEO Mega-Constellations and GNSS in Urban Canyons

Effects of Strong Geomagnetic Storms on the Ionosphere and Degradation of Precise Point Positioning Accuracy during the 25th Solar Cycle Rising Phase: A Case Study

Approaching the peak year of the 25th solar activity cycle, the frequency of strong geomagnetic storms is gradually increasing, which seriously affects the navigation and positioning performance of GNSS. Based on the globally distributed GNSS station data and FORMOSAT-7/COSMIC-2 occultation data, this paper explores for the first time the effects of the G4-class geomagnetic storm that occurred on 23–24 April 2023 on the global ionosphere, especially the ionospheric equatorial anomalies and F-layer perturbations. It reveals the precise point positioning (PPP) accuracy degradation during a geomagnetic storm. The results show that the ionospheric rate of total electron content index (ROTI) and near high latitude GNSS phase scintillations index have varying levels of perturbation during geomagnetic storms, with the maximum ROTI and phase scintillations index exceeding 0.5 TECU/min and 0.8, respectively. The equatorial ionization anomaly (EIA) shows an enhanced state (positive ionospheric storms) during geomagnetic storms, and the cause of this phenomenon is most likely the equatorward neutral wind. The variation of the S4 index of the FORMOSAT-7/COSMIC-2 satellite reveals the uplift of the F-layer during geomagnetic storms. During geomagnetic storms, the PPP accuracy degrades most seriously at high latitudes, the maximum MAE exceeds 2.3 m, and the RMS in the three-dimensional (3D) direction exceeds 2.0 m. These investigations can provide case support for space weather and GNSS studies of the impact of geomagnetic storms during peak solar activity years.

GALILEO HAS – FIRST PERFORMANCE TESTS DURING ITS INITIAL PHASE OF OPERATION

Galileo High Accuracy Service (HAS) became available in January 2023. As declared, in its final operational capability, it should be able to provide to users the Precise Point Positioning (PPP) at horizontal accuracy level better than 20 cm in real-time with 95% confidence globally. At the moment Galileo HAS works in its initial phase of operation with some limitations regarding its availability, convergence time and accuracy but gives the chance to observe the performance of positioning tool at the accuracy level which was available before by using differential measurement only. Galileo HAS PPP, free of charge and based only on satellite signals delivered by nominal Galileo constellation is unique in its kind between various GNSS positioning modes. This article presents the results of first, preliminary tests on Galileo HAS performance conducted in July 2023 in Gdynia, Poland. The field tests were conducted with Galileo HAS capable receiver in static conditions and focused on the verification the declared service performance in the real positioning scenarios. Additionally, the Galileo HAS PPP performance was compared with the simultaneous performance of other GNSS positioning methods such as EGNOS, DGPS, dual frequency GPS+Galileo or dual frequency GPS and dual frequency Galileo. This first experiences with Galileo HAS positioning should show all potential users what performance level can be achieved with this new, unique in its kind GNSS positioning method at the present state of its implementation.

Structure and performance analysis of fusion positioning system with a single 5G station and a single GNSS satellite

ABSTRACT NaGlobal vigation Satellite System (GNSS) positioning technology is widely used for its high precision, global, and all-weather service. However, in complex environments such as urban canyons, GNSS performance is often degraded due to signal occlusion and even fails to achieve positioning due to the insufficient visible satellites. Because of the characteristics of large bandwidth, low latency, and high Base Station (BS) density, the fifth-Generation mobile communication (5G) technology has gradually become a trend for positioning in cities while offering traditional communication service. To supply the communication demands of the User Equipment (UE), only one BS is usually considered to establish a connection with the UE during the BS construction. However, the positioning accuracy with a single BS in urban canyons will be significantly reduced. To further improve the positioning accuracy in such extreme scenarios, this paper proposes a simplified 5G/GNSS fusion positioning system architecture using observations from only a 5G BS and a GNSS satellite. In this system, the GNSS receiver is mounted on the 5G BS, and the measurements provided by the receiver are used to form the differential code and complete the position estimation. The positioning mathematical models of the system based on the original code and differential code are derived. Then, the impacts of the measurements noise and the time synchronization error on the positioning accuracy are analyzed theoretically. Finally, the positioning performance is investigated by a set of simulation experiments. Numerical results show that under the existing 5G measurement noise and 2 m’s code measurement noise, the improvement of the differential code based fusion positioning compared with the 5G-only positioning is more than 32%, which is also about 6% higher than the original code based fusion positioning. Besides, this improvement is not affected by the time synchronization error between the BS and the GNSS satellite.

On Mitigating the Effects of Multipath on GNSS Using Environmental Context Detection

Accurate, ubiquitous and reliable navigation can make transportation systems (road, rail, air and marine) more efficient, safer and more sustainable by enabling path planning, route optimization and fuel economy optimization. However, accurate navigation in urban contexts has always been a challenging task due to significant chances of signal blockage and multipath and non-line-of-sight (NLOS) signal reception. This paper presents a detailed study on environmental context detection using GNSS signals and its utilization in mitigating multipath effects by devising a context-aware navigation (CAN) algorithm that detects and characterizes the working environment of a GNSS receiver and applies the desired mitigation strategy accordingly. The CAN algorithm utilizes GNSS measurement variables to categorize the environment into standard, degraded and highly degraded classes and then updates the receiver’s tracking-loop parameters based on the inferred environment. This allows the receiver to adaptively mitigate the effects of multipath/NLOS, which inherently depend upon the type of environment. To validate the functionality and potential of the proposed CAN algorithm, a detailed study on the performance of a multi-GNSS receiver in the quad-constellation mode, i.e., GPS, BeiDou, Galileo and GLONASS, is conducted in this research by traversing an instrumented vehicle around an urban city and acquiring respective GNSS signals in different environments. The performance of a CAN-enabled GNSS receiver is compared with a standard receiver using fundamental quality indicators of GNSS. The experimental results show that the proposed CAN algorithm is a good contributor for improving GNSS performance by anticipating the potential degradation and initiating an adaptive mitigation strategy. The CAN-enabled GNSS receiver achieved a lane-level accuracy of less than 2 m for 53% of the total experimental time-slot in a highly degraded environment, which was previously only 32% when not using the proposed CAN.

Maximum eigenvalue detection for local ionospheric anomaly - theory, cases, statistics, and potential application

At low latitudes in China, local ionospheric anomalies are frequent and difficult to capture, posing positioning errors and safety risks to GNSS users. This leads to conservative error bounds in GNSS augmentation systems. For example, in Satellite Based Augmentation System (SBAS), the presence of under-sampled regions and the ionospheric instability at low latitudes can result in an over-conservative error bound, i.e., Grid Ionospheric Vertical Error (GIVE) with reduced availability. Ionospheric irregularity detectors could be used to exclude anomalies from the grid model to share the integrity risk and tighten the GIVE. The detection method needs to have theoretical validity and sensitivity to small local anomalies. However, current irregularity detectors are designed for Ionospheric Grid Point (IGP), dealing with wide-area spatial anomalies. The problem of decreased availability resulting from the over-conservative error bound caused by the frequent local ionospheric anomalies is unsolved, especially at low latitudes and the equatorial region. To further enhance the GNSS performance, the applicability analysis of a maximum eigenvalue-based ionospheric irregularity detector, which is sensitive to local-scale spatial anomalies, is presented. The detection capability of MED for ionospheric anomalies is demonstrated by theory, cases, statistics, and simulation applications. This method can also be used for ionospheric monitoring in geodesy or geophysics.

Kinematic Galileo and GPS Performances in Aerial, Terrestrial, and Maritime Environments

On 15 December 2016, the European Commission (EC) declared the provision of the Galileo Initial Services (IS). This marked a historical milestone in the Galileo program, towards the reaching of its Full Operational Capability. This allows users to navigate with performance-accuracy levels either matching or exceeding those obtained with other GNSS. Under the delegation of the EC, the European Union Agency for the Space Programme (EUSPA) has assumed the role of the Galileo Service Provider. As part of this service provision, the primary mission of the Galileo Reference Centre (GRC) is to provide the EUSPA and the EC with independent means for monitoring and evaluating the performance of the Galileo services, the quality of the signals in space, and the performance of other GNSS. This mission includes significant contributions from cooperating entities in the European Union (EU) Member States (MS), Norway and Switzerland. In particular, for a detailed assessment of the Galileo performance, these contributions include (but are not limited to) periodic dynamic campaigns in three different environments (aerial, terrestrial, and maritime). These campaigns were executed in the frame of the GRC-MS Project and use multi-constellation receivers to compare the navigation performance obtained with different GNSS. The objective of this paper is to present the numerical results obtained from these campaigns, together with several considerations about the experimental setup, the methodology for the estimation of the reference («actual») trajectory, and the reasons for possible performance degradations.

Three time spoofing algorithms for GNSS timing receivers and performance evaluation

Three time spoofing algorithms for GNSS timing receivers and performance evaluation

Analysis of the differences in the messages broadcast by different GEOs of WAAS

The Wide Area Augmentation System(WAAS) is the most mature satellite-based augmentation system currently available to provide higher performance navigation and positioning services for civil aviation users. WAAS broadcasts a wide range of differential correction data and integrity information to users via Geostationary Orbit(GEO) satellites to achieve enhanced navigation performance of GNSS. This paper selects the enhanced messages broadcast by different GEO satellites from February 1st to February 7th, 2022, decodes and compares the data of the messages MT2-5 and MT25, and analyzes the differences of the messages broadcast by different GEOs.

Smartphone GNSS Performance in an Urban Scenario with RAIM Application.

In an urban scenario, GNSS performance is strongly influenced by gross errors in the measurements, usually related to multipath and non-line-of-sight phenomena. The use of RAIM algorithms is a common approach to solve this issue. A significant amount of the existing GNSS receivers is currently mounted on smart devices, above all, smartphones. A typical drawback of these devices is the unavailability of raw measurements, which does not allow fully exploiting the GNSS potential; in particular, this feature limits the use of RAIM algorithms. Since 2016, for few smart devices, it has been finally possible to access GNSS raw measurements, allowing the implementation of specific algorithms and enabling new services. The Xiaomi Mi 8 is equipped with the Broadcom BCM47755 receiver, able to provide dual-frequency raw measurements from quad-constellation GPS, Glonass, Galileo, BeiDou. In this work, the performance in an urban area of the Xiaomi Mi8 GNSS was analyzed. An important issue of smartphone GNSS is related to the antenna, which is not able to protect from the multipath phenomenon; this issue has a large probability to emerge in hostile environments like urban areas. As a term of comparison, the high-sensitivity receiver NVS NV08C-CSM, connected to a patch antenna, was used. In particular, the considered receivers were placed in the same location, and their positions were estimated in single point positioning, applying a classical RAIM algorithm. An error analysis was carried out, and the obtained results demonstrated the effectiveness of RAIM when applied to Xiaomi Mi8 GNSS measurements.

Initial Results of Modeling and Improvement of BDS-2/GPS Broadcast Ephemeris Satellite Orbit Based on BP and PSO-BP Neural Networks

With the rapid development and gradual perfection of GNSS in recent years, improving the real-time service performance of GNSS has become a research hotspot. In GNSS single-point positioning, broadcast ephemeris is used to provide a space–time reference. However, the orbit parameters of broadcast ephemeris have meter-level errors, and no mathematical model can simulate the variation of this, which restricts the real-time positioning accuracy of GNSS. Based on this research background, this paper uses a BP (Back Propagation) neural network and a PSO (Particle Swarm Optimization)–BP neural network to model the variation in the orbit error of GPS and BDS broadcast ephemeris to improve the accuracy of broadcast ephemeris. The experimental results showed that the two neural network models in GPS can model the broadcast ephemeris orbit errors, and the results of the two models were roughly the same. The one-day and three-day improvement rates of RMS(3D) were 30–50%, but the PSO–BP neural network model was better able to model the trend of errors and effectively improve the broadcast ephemeris orbit accuracy. In BDS, both of the neural network models were able to model the broadcast ephemeris orbit errors; however, the PSO–BP neural network model results were better than those of the BP neural network. In the GEO satellite outcome of the PSO–BP neural network, the STD and RMS of the orbit error in three directions were reduced by 20–70%, with a 20–30% improvement over the BP neural network results. The IGSO satellite results showed that the PSO–BP neural network model output accuracy of the along- and radial-track directions experienced a 70–80% improvement in one and three days. The one- and three-day RMS(3D) of the MEO satellites showed that the PSO–BP neural network has a greater ability to resist gross errors than that of the BP neural network for modeling the changing trend of the broadcast ephemeris orbit errors. These results demonstrate that using neural networks to model the orbit error of broadcast ephemeris is of great significance to improving the orbit accuracy of broadcast ephemeris.

Prediction on the Urban GNSS Measurement Uncertainty Based on Deep Learning Networks With Long Short-Term Memory

The GNSS performance could be significantly degraded by the interferences in an urban canyon, such as the blockage of the direct signal and the measurement error due to reflected signals. Such interferences can hardly be predicted by statistical or physical models, making urban GNSS positioning unable to achieve satisfactory accuracy. The deep learning networks, specializing in extracting abstract representations from data, may learn the representation about the GNSS measurement quality from existing measurements, which can be employed to predict the interferences in an urban area. In this study, we proposed a deep learning network architecture combining the conventional fully connected neural networks (FCNNs) and the long short-term memory (LSTM) networks, to predict the GNSS satellite visibility and pseudorange error based on GNSS measurement-level data. The performance of the proposed deep learning networks is evaluated by real experimental data in an urban area. It can predict the satellite visibility with 80.1% accuracy and predict the pseudorange errors with an average difference of 4.9 meters to the labeled errors. Experiments are conducted to investigate what representations have been learned from data by the proposed deep learning networks. Analysis results show that the LSTM layer within the proposed networks may contain representations about the environment, which affects the prediction behavior and can associate with the real environment information.

Performance assessment of GNSS diffraction models in urban areas

<h3>Abstract</h3> The GNSS performance is significantly degraded in urban canyons because of the signal interferences caused by buildings. Besides the multipath and nonline-of-sight (NLOS) receptions, the diffraction effect frequently occurs in urban canyons, which will severely attenuate the signal strength when the satellite line-of-sight (LOS) transmitting path is close to the building edge. It is essential to evaluate the performance of current diffraction models for GNSS before applying mitigation. The detailed steps of applying the knife-edge model and the uniform geometrical theory of diffraction (UTD) model on GNSS are given, including the 𝐶∕𝑁₀ and pseudorange simulation of the diffracted signal. The performances of both models are assessed using real data from two typical urban scenarios. The result shows the UTD can adequately model the GNSS diffraction effect even in a complicated urban area. Compared with the knife-edge model, the UTD achieves better modeling accuracy, whereas it requires higher computational loads.

ROTI maps of Greenland using kriging

Abstract GNSS satellite signals are affected by the media when traversing Earth’s atmosphere, and the performance of GNSS based positioning and navigation is correlated with these effects. In the ionosphere, the signals are affected by the number of electrons along the signal path which can be quantified by the total electron content. The focus of this article is scintillation effects caused by electrons in the Arctic ionosphere, and the rate of the total electron content index, the ROTI, is used as a measure of the scintillation. Data from permanent GNSS reference stations in Greenland is used to generate maps of the ROTI in Greenland, and the novelty of the work in this paper is the application of the ordinary kriging method as the basis for ROTI maps in the Arctic. Further, the choice of satellite constellations as well as the elevation mask used in the data analyses are analyzed and discussed. Also, the performance of using ordinary kriging for ROTI maps during times with both a low and a very high geomagnetic activity are discussed. The results show that ordinary kriging performs well during high geomagnetic activity, while during low activity the natural neighbor interpolation method is a better choice for the Arctic.

PRESENT-DAY APPROACHES TO FULL-SCALE TRIAL METHODS FOR DYNAMIC SHIP SQUAT DETERMINATION

The article defines necessity to use ship squat when computing underkeel clearance. Review of full-scale trials methods for squat with the use of global navigational sattelite systems was made. Sources of method’s errors were analyzed and its values were evaluated. Justification of necessity to ajust trial methods has been given, based on inland waterways emvironment condtions of Gorodets – Kstovo route and performance of GNSS in this area. The authors defined parameters to be measured during full-scale trials for the purpose of numerical methods improvement.

Performance evaluation of real-time tightly-coupled GNSS PPP/MEMS-based inertial integration using an improved robust adaptive Kalman filter

Abstract Typically, the extended Kalman filter (EKF) is used for tightly-coupled (TC) integration of multi-constellation GNSS PPP and micro-electro-mechanical system (MEMS) inertial navigation system (INS) to provide precise positioning, velocity, and attitude solutions for ground vehicles. However, the obtained solution will generally be affected by both of the GNSS measurement outliers and the inaccurate modeling of the system dynamic. In this paper, an improved robust adaptive Kalman filter (IRKF) is adopted and used to overcome the effect of the measurement outliers and dynamic model errors on the obtained integrated solution. A real-time IRKF-based TC GPS+Galileo PPP/MEMS-based INS integration algorithm is developed to provide precise positioning and attitude solutions. The pre-saved real-time orbit and clock products from the Centre National d’Etudes Spatials (CNES) are used to simulate the real-time scenario. The performance of the real-time IRKF-based TC GNSS PPP/INS integrated system is assessed under open sky environment, and both of simulated partial and complete GNSS outages through two ground vehicular field trials. It is shown that the real-time TC GNSS PPP/INS integration through the IRKF achieves centimeter-level positioning accuracy under open sky environments and decimeter-level positioning accuracy under GNSS outages that range from 10 to 60 seconds. In addition, the use of IRKF improves the positioning accuracy and enhances the convergence of the integrated solution in comparison with the EKF. Furthermore, the IRKF-based integrated system achieves attitude accuracy of 0.052°, 0.048°, and 0.165° for pitch, roll, and azimuth angles, respectively. This represents improvement of 44 %, 48 %, and 36 % for the pitch, roll, and azimuth angles, respectively, in comparison with the EKF-based counterpart.

Characteristics of Ionospheric Irregularities Using GNSS Scintillation Indices Measured at Jang Bogo Station, Antarctica (74.62°S, 164.22°E)

AbstractGlobal Navigation Satellite System (GNSS) signals strongly depend on the ionospheric conditions, which are composed of electrons and ions generated by solar radiation and particle precipitation. Ionospheric plasma irregularities may cause the scintillation of the GNSS signals or even the loss of signal lock, resulting in the reduction of positioning accuracy and timing precision. Phase scintillation phenomenon is known to occur frequently at high latitudes and primarily related to a significant plasma density gradient, which is due to fast plasma flows in the polar region, energetic particle precipitation in the auroral region, polar cap patches, or several instability mechanisms. Statistical studies are required to understand the characteristics of ionospheric (both phase and amplitude) scintillations at high latitudes. Here, we report the results of ionospheric scintillation measurements at Jang Bogo Station (JBS; 74.62°S, 164.22°E), located inside the polar cap region in Antarctica. The occurrence rates of ionospheric scintillations over the JBS are recorded for 2 years (2017–2018) during solar minimum conditions. The occurrence rates of amplitude scintillations increase only at lower elevation angles (below 30°), which are hard to determine whether the source is ionospheric irregularity or ambient noise such as multipath. In contrast, the occurrence rates of phase scintillations depend on the azimuth angle, season, magnetic activity, magnetic local time, and signal frequency. The results of our analysis suggest that users of the GNSS should consider these parameters to prepare for the degradation of the GNSS performance at high latitudes in the Southern Hemisphere.

Low-latitude GNSS ionospheric scintillation dependence on magnetic field orientation and impacts on positioning

Ionospheric scintillation often occurs in equatorial and low-latitudes regions between ± 20° geomagnetic latitude and impacts GNSS performance on geodetic applications. In equatorial and low latitude regions, scintillation on the GNSS signal occurs mainly due to small-scale irregularities inside plasma bubbles that are magnetic field-aligned structures. We derived the propagation angle between GNSS ray paths and magnetic field lines to quantify scintillation occurrences of multi-constellation GNSS signals in relation to magnetic field orientation. Precise point positioning (PPP) solutions are obtained to assess the field-aligned scintillation signal impacts on positioning. A case study based on observations in Hong Kong is conducted to characterize a typical low-latitude region near the northern equatorial anomaly crest. Measurements from multiple GNSS constellations, i.e., GPS, GLONASS, Galileo and BDS are used. Results suggest that the GNSS scintillation intensity is enhanced in the local southern sky within the azimuth range of 150°–240° with peak at ~ 180°, where the signal paths closely align with the magnetic field lines. Analysis of the data show that up to five GPS satellites may have their signal paths aligned closely with magnetic field lines simultaneously. This can result in an increase in the kinematic PPP errors from several centimetres to tens of meters. The relationship between the scintillation occurrence and magnetic field orientation could be exploited in the future to mitigate scintillation effects on GNSS applications.