Global Navigation Satellite System Users Research Articles

3D Galileo Reference Antenna Pattern for Space Service Volume Applications.

There is an increasing demand for navigation capability for space vehicles. The exploitation of the so-called Space Service Volume (SSV), and hence the extension of the Global Navigation Satellite System (GNSS) from terrestrial to space users, is currently considered a fundamental step. Knowledge of the constellation antenna pattern, including the side lobe signals, is the main input for assessing the expected GNSS signal availability and navigation performance, especially for high orbits. The best way to define and share this information with the final GNSS user is still an open question. This paper proposes a novel methodology for the definition of a high-fidelity and easy-to-use statistical model to represent GNSS constellation antenna patterns. The reconstruction procedure, based on antenna characterization techniques and statistical learning, is presented here through its successful implementation for the "Galileo Reference Antenna Pattern (GRAP)" model, which has been proposed as the reference model for the Galileo programme. The GRAP represents the expected Equivalent Isotropic Radiated Power (EIRP) variation for the Galileo FOC satellites, and it is obtained by processing the measurements retrieved during the characterization campaign performed on the Galileo FOC antennas. The mathematical background of the model is analyzed in depth in order to better assess the GRAP with respect to different objectives such as improved resolution, smoothness and proper representation of the antenna pattern statistical distribution. The analysis confirms the enhanced GRAP properties and envisages the possibility of extending the approach to other GNSSs. The discussion is complemented by a preliminary use case characterization of the Galileo performance in SSV. The accessibility, a novel indicator, is defined in order to represent in a quick and compact manner, the expected Galileo SSV quality for different altitudes and target mission requirements. The SSV characterization is performed to demonstrate how simply and effectively the GRAP model can be inserted into user analysis. The work creates the basis for an improved capability for assessing Galileo-based navigation in SSV according to the current knowledge of the antenna pattern.

Evaluating the single-frequency static precise point positioning accuracies from multi-constellation GNSS observations at an Indian low-latitude station

Abstract Multiple constellations and their combinations in the global navigation satellite systems (GNSS) provide a great opportunity for single-station precise point positioning (PPP) models. The PPP models are of more importance for GNSS users as they are cost-effective with reasonable accuracy. There are abundant models in the market that use different data processing techniques based on the location and constellations used. In this study, we used the precise point positioning (PPP) software Net_Diff to verify the positioning accuracy at a low latitude Indian location using individual global satellite constellations (GPS, GLONASS, Galileo, BeiDou) and their combinations with GPS fixed. The ionospheric correction models such as GIM and Klobuchar are applied in the post-processing to determine the positioning accuracy. The Kalman filter method is applied to model the input data along with including the noise to derive the position solution. The results revealed that the GPS showed constant residual error for both quiet and disturbed days. In terms of single constellation Galileo produced less residuals in WGS 84 and ECEF coordinate systems whereas in the multi-constellation combination GPS, Galileo and GLONASS resulted in residuals of lesser magnitudes compared to the other combinations considered in this study. The RMS and STD of the residuals confirmed the high precision for Galileo and low precision for BeiDou constellations at the location.

Code observation-specific biases estimation for the modernized multi-GNSS and multi-frequency signals: An approach considering signal distortion biases

With the continuous development of global navigation satellite systems (GNSS) modernization, the code bias presented in the form of observation-specific biases (OSB) is more flexible and effective when processing modern multi-frequency and multi-GNSS signals, and therefore widely accepted by the GNSS community. However, the newly reported signal distortion biases (SDB) are ignored in the existing OSB estimation methods, which may affect the reliability of the final OSB estimation. In addition, the existing studies about SDB estimation are independent of OSB estimation, and thus a set of SDB products is generated independent of OSB products, which undoubtedly brings more complicated correction operations to GNSS users. In view of it, this study proposes an approach to code OSB estimation for multi-frequency and multi-GNSS arbitrary signals by reparameterization, which considers the SDB parameter. The aim of this study is to generate a set of code OSB products that take into account SDB parameters for the GNSS users to use. Due to considering the influence of SDB on raw code observations, the OSB estimation obtained by the proposed method is related to specific satellite-receiver pairs, which makes it different from the traditional OSB estimation methods. To achieve this, an extended model for multi-frequency and multi-GNSS arbitrary signal is first established based on the undifferenced and uncombined model, in which the SDB parameter is taken into account by re-parameterization. Based on the proposed model, three types of code bias that contain the OSB information can be obtained for the subsequent OSB estimation. Then, the three types of code bias in the first step are used as virtual observations for multi-frequency and multi-GNSS arbitrary signal OSB estimation through a two-step method. The proposed method is validated with a whole month of real measured data from 418 stations in MGEX and GA CORS to generate OSBs for GPS, GLONASS, and Galileo. The comparison between the estimated OSBs and the OSB products from CAS indicates the reliability of the proposed method. Besides, all types of OSB for four receiver groups are generated based on the proposed method to analyze the relationship between OSB and receiver groups. Results indicate that the estimated OSBs are related to receiver groups, and specific differences exist between different satellites and GNSS signals. It also proves that the OSB estimation is biased by the inconsistencies of the deviation in different receiver groups, which is more obvious for GLONASS.

MLP-based user-applicable method for SBAS GIVD calibration: A comparative study based on CODE final GIM products

Satellite-Based Augmentation Systems (SBASs) are designed to enhance the performance of Global Navigation Satellite Systems (GNSSs) for civil aviation users. As SBAS Geostationary Earth Orbit (GEO) satellite signals are received in a wide area, far more non-aeronautical GNSS users utilize SBAS to improve navigation performance. Since ionospheric delay is the principal error source of GNSS and a leading correction aspect of SBAS, the GEO-broadcast ionospheric data quality of six SBASs over the past three years is assessed in this article. Results show that European Geostationary Navigation Overlay Service (EGNOS), System for Differential Correction and Monitoring (SDCM), and Wide-Area Augmentation System (WAAS) have the highest Grid Ionospheric Vertical Delay (GIVD) accuracy judged by the residual Standard Deviation (STD), then followed by BeiDou SBAS (BDSBAS) and Multi-functional Satellite Augmentation System (MSAS), while GPS-Aided GEO Augmented Navigation (GAGAN) is the worst. The 6 m Grid Ionospheric Vertical Error (GIVE) availability is over 90 percent of the time for most Ionospheric Grid Points (IGPs) of all tested SBASs. However, GAGAN and WAAS have a significant availability decline at 3 m GIVE. In addition, the integrity limits of MSAS and WAAS are fairly conservative. In contrast, the confidence bounds of BDSBAS and SDCM are excessively radical that fail to meet the integrity requirement. To improve the ionospheric data quality received from SBAS, a Multi-Layer Perceptron (MLP)-based user-applicable GIVD calibration method is proposed in the article. A well-trained MLP learned temporal and spatial correlations of the IGP delays and extracted transfer functions between broadcast and reference GIVDs to eliminate error. The SBAS processing errors in Differential Code Bias (DCB) compensation, GIVD estimation modeling, and GEO message quantization are rectified by the MLP trained by abundant historical data with Center for Orbit Determination in Europe (CODE) final Global Ionospheric Maps (GIMs) as reference. Test results on real-time data show that over 85 percent IGPs have STD decline after calibration. The STD declination rates of six SBASs except for SDCM are over 15 percent, and the Mean Absolute Error (MAE) and Root Mean Square Error (RMS) calibration effects are dramatic for all systems. Finally, the average GIVEs are reduced by more than 50 percent for EGNOS, GAGAN, MSAS, and WAAS with a 99.9 percent integrity level maintained. Despite no promotion on availability for BDSBAS and SDCM, the proposed method compensates for the integrity issues of the systems.

High-Accuracy Absolute-Position-Aided Code Phase Tracking Based on RTK/INS Deep Integration in Challenging Static Scenarios

Many multi-sensor navigation systems urgently demand accurate positioning initialization from global navigation satellite systems (GNSSs) in challenging static scenarios. However, ground blockages against line-of-sight (LOS) signal reception make it difficult for GNSS users. Steering local codes in GNSS basebands is a desirable way to correct instantaneous signal phase misalignment, efficiently gathering useful signal power and increasing positioning accuracy. Inertial navigation systems (INSs) have been used as effective complementary dead reckoning (DR) sensors for GNSS receivers in kinematic scenarios, resisting various forms of interference. However, little work has focused on whether INSs can improve GNSS receivers in static scenarios. Thus, this paper proposes an enhanced navigation system deeply integrated with low-cost INS solutions and GNSS high-accuracy carrier-based positioning. First, an absolute code phase is predicted from base station information and integrated solutions of the INS DR and real-time kinematic (RTK) results through an extended Kalman filter (EKF). Then, a numerically controlled oscillator (NCO) leverages the predicted code phase to improve the alignment between instantaneous local code phases and received ones. The proposed algorithm is realized in a vector-tracking GNSS software-defined radio (SDR). Results of the time-of-arrival (TOA) and positioning based on real-world experiments demonstrated the proposed SDR.

Low-Cost GNSS Simulators With Wireless Clock Synchronization for Indoor Positioning

In regions where global navigation satellite systems (GNSS) signals are unavailable, such as underground areas and tunnels, GNSS simulators can be deployed for transmitting simulated GNSS signals. Then, a GNSS receiver in the simulator coverage outputs the position based on the received GNSS signals (e.g., Global Positioning System (GPS) L1 signals in this study) transmitted by the corresponding simulator. This approach provides periodic position updates to GNSS users while deploying a small number of simulators without modifying the hardware and software of user receivers. However, the simulator clock should be synchronized to the GNSS satellite clock to generate almost identical signals to the live-sky GNSS signals, which is necessary for seamless indoor and outdoor positioning handover. The conventional clock synchronization method based on the wired connection between each simulator and an outdoor GNSS antenna causes practical difficulty and increases the cost of deploying the simulators. This study proposes a wireless clock synchronization method based on a private time server and time delay calibration. Additionally, we derived the constraints for determining the optimal simulator coverage and separation between adjacent simulators. The positioning performance of the proposed GPS simulator-based indoor positioning system was demonstrated in the underground testbed for a driving vehicle with a GPS receiver and a pedestrian with a smartphone. The average position errors were 3.7 m for the vehicle and 9.6 m for the pedestrian during the field tests with successful indoor and outdoor positioning handovers. Since those errors are within the coverage of each deployed simulator, it is confirmed that the proposed system with wireless clock synchronization can effectively provide periodic position updates to users where live-sky GNSS signals are unavailable.

POINT POSITIONING PERFORMANCE OF TRIMBLE-RTX IN DIFFERENT SATELLITE COMBINATIONS

Today, new global positioning algorithms, techniques and technologies are emerging thanks to services such as International Global Navigation Satellite Systems (GNSS) Service (IGS) that offer orbit and clock correction data of satellite systems to all GNSS users. These solutions are developed in order to eliminate the disadvantages of current positioning techniques such as requiring more than one GNSS receiver and not exceeding a certain distance between the reference station and the rover. One of these innovative technology products is Trimble CenterPoint RTX Post-Processing (Trimble-RTX) technology. In this study, the point positioning performance of the Trimble-RTX service was investigated. The 31-day RINEX data obtained from 2 IGS stations are used in 4 different satellite combinations (GPS (G), GPS+GLONASS (G+R), GPS+GALILEO (G+E), GPS+GLONASS+GALILEO (G+R+E)) processed with Trimble-RTX. By comparing the obtained coordinates with the coordinates of the stations published by IGS, the accuracy and precision of the coordinates were evaluated for each satellite combination. As a result of the evaluation, it was seen that there were generally no significant differences between the results obtained from 4 different satellite combinations at the stations.

NeQuick2 validation using multi-satellite and ground data

Global Navigation Satellite System’s (GNSS) positioning calculation is prone to ionospheric errors. Single frequency GNSS users receive ionospheric corrections through broadcast ionospheric models. Therefore, the accuracy of ionospheric models must be validated based on various geographic and geomagnetic conditions. In this work, an attempt is made to validate NeQuick2 electron density (Ne) using multiple sources of space-based and ground-based data at the Arabian Peninsula and for low solar activity conditions. These sources include space-based data from Swarm, DMSP and COSMIC-2 satellite constellations and ground-based data from GNSS receiver and the ionosonde. The period of this study is 1 year from October 2019 to September 2020. Analysis shows that the agreement between NeQuick2 and experimental Ne close to the peak density height depends on seasons and time of the day with the largest errors found in Autumn and during the daytime. NeQuick2 generally overestimates Ne during the daytime. During the early morning and evening hours, Ne estimates seem to be fairly accurate with slight underestimation in Winter and Spring. Estimation of slab thickness by NeQuick2 is found to be close to the values calculated using collocated ionosonde and GNSS receiver.

Modeling and analysis of an ionospheric mapping function considering azimuth angle: A preliminary result

Generally, dual- and multi-frequency global navigation satellite system (GNSS) users can use dual- or multi-frequency combinations to eliminate the ionospheric delay. However, different vertical ionospheric models are applied for single-frequency GNSS users, which need an ionospheric mapping function for conversion. Although many mapping functions can be employed, the influence of latitude, azimuth, solar flux, and other factors are not taken into account. Thus, we proposed a mapping function, named SGG-MF, considering the influence of azimuth. The conversional results of single-layer model mapping function (SLM-MF), Klobuchar mapping function (Klobuchar-MF), modified single layer model mapping function (MSLM-MF) and SGG-MF are evaluated by using coinciding pierce point (CPP) technique as well as single-frequency precise point positioning (SF-PPP) in static mode. For the CPP technique, it is found that the mean absolute errors (MAE) of SLM-MF, Klobuchar-MF, and, MSLM-MF range from 1.5 to 2.1 TECU (total electron content unit), while SGG-MF ranges from 1.5 to 1.7 TECU. The standard deviation (STD) of SGG-MF improved by about 13.6%, 14.9%, and 13.6% compared with that of SLM-MF, Klobuchar-MF, and MSLM-MF, respectively. For the SF-PPP test, the positioning error of SGG-MF was reduced by about 6.0%, 22.9%, and 11.9% compared with that of SLM-MF, Klobuchar-MF, and MSLM-MF, respectively.

Vertical Protection Level Optimization and Availability Analysis for Advanced RAIM

With the introduction of global navigation satellite systems (GNSSs) in aviation, there has been increased dependency on GNSS position. Multi-constellation GNSS services and equipment will remain a solution for many aircraft positions in safety. Multi-constellation GNSS can improve robustness and navigation performance. Therefore, advanced receiver autonomous integrity monitoring (advanced RAIM or ARAIM) technology is being developed as an augmentation method for GNSS users under multi-constellation. ARAIM can allow increased service level globally and provide vertical guidance during the approach phase for aircrafts. Since the traditional ARAIM algorithm uses the average allocation strategy to allocate integrity and continuity risk, an allocation approach based on the particle swarm optimization (PSO) algorithm is presented in this article. Different allocation strategies for integrity and continuity risk are chosen as different particles, and the weighted sum of vertical protection level corresponding to different fault subsets is selected as the fitness function to optimize the allocation strategy and the corresponding VPL. Based on real GNSS data, the ARAIM algorithm under multi-constellation is analyzed. The experimental results demonstrate that the integrity and continuity risk allocation method based on the proposed algorithm optimizes the VPL and improves the global availability of ARAIM under multi-constellation.

SVR and ARIMA models as machine learning solutions for solving the latency problem in real-time clock corrections

Real-time precise point positioning (PPP) has become a prevalent technique in global navigation satellite systems (GNSS). However, GNSS real-time users must receive space state representation (SSR) products to correct for satellite clock, orbit, and phase biases. The International GNSS Service (IGS) provides GNSS users with real-time services (RTSs) through different real-time correction SSR products. These products arrive at the GNSS users with some latency, which affects the quality of real-time PPP positioning. The autoregressive integrated moving average (ARIMA) and support vector regression (SVR) models are used in this research to predict those corrections to eliminate the latency effect. ARIMA model reduces the standard deviation by 28% and 13% for GPS and GLONASS constellations, respectively, compared to the real-time solution, which includes the latency effect, the research simulated the latency effect and named it a forced-latency solution, and the SVR model reduces the standard deviation by 28% and 23% for GPS and GLONASS constellations, respectively. The results for the permanent GNSS stations used in this study across different years 2013, 2014, 2015, 2019, and 2021 show a mean reduction in the 3D positioning standard deviation by 13% compared with the forced-latency solution for the ARIMA solution and 9% for the SVR solution. The potential of both models to overcome the latency effect is apparent based on the findings.

ASSESSING QUALITY OF CORSNET-NSW INFRASTRUCTURE FOR USE IN REGIONAL NEW SOUTH WALES, AUSTRALIA

Abstract. CORSnet-NSW is a network of Global Navigation Satellite System (GNSS) Continuously Operating Reference Stations (CORS) covering the state of NSW and providing centimetre-level real-time positioning. This research paper aims to determine the level of accuracy and precision of CORSnet-NSW in regional parts of the network and compare them to that of traditional RTK under identical conditions. It investigates what effects satellite geometry and proximity to a CORS station have on NRTK measurements. It also verifies the CORSnet-NSW claim of network wide 2cm accuracy. The claim was found to be true at the 68% Confidence Interval. Changes in satellite geometry were not found to affect the results for the most part. It was also found that CORSnet-NSW precision was affected by the proximity of the rover to the base/calibration points more than its proximity to a CORSnet-NSW station. However, even though the CORSnet-NSW results were better than expected, traditional RTK remains the most precise and consistent method. This research paper provides GNSS users in regional NSW with the evidence they need to make informed decisions regarding which type of RTK method is fit for their purposes.

Farklı troposfer modellerinin gerçek zamanlı çoklu-GNSS PPP performansına etkisi

With the initialization of IGS (International GNSS Service) real-time service products, real-time Precise Point Positioning (PPP) applications have been a popular topic within the GNSS (Global Navigation Satellite Systems) users. The impact of the troposphere on GNSS signals is one of the most crucial error sources regarding the real-time PPP solution. In the PPP technique, the dry component of tropospheric delay is usually corrected by means of empirical models, while its wet component is estimated as an unknown parameter in the adjustment process. Hence, the troposphere model employed in the PPP solution has a considerable impact on the performance of the obtained solution. Therefore, the main objective of this study is to investigate the impact of different troposphere models on the performance of real-time multi-GNSS PPP. As a part of this study, four different troposphere models, where Saastamoinen and Hopfield models that are most frequently used in GNSS solutions are used together with GPT (Global Pressure and Temperature) 2 and 3 models separately, were constituted. In this context, the observation dataset acquired from a total of 16 different IGS stations over a ten-day period of December 19-28, 2021, were processed utilizing four different troposphere models. In addition to the positioning performance, PPP solutions were also analyzed in terms of zenith total delay (ZTD) estimation. The results show that the best positioning performance can be obtained when the Saastamoinen model is used in combination with GPT3. The three-dimensional positioning accuracy acquired from the corresponding solution is 2.72 cm, which is better than the closest solution by a ratio of 9.2%. Besides, in terms of the ZTD estimation, the best performance is achieved again in the case when the Saastamoinen model is used in combination with GPT3. For the related solution, the accuracy of ZTD estimation is calculated as 1.24 cm and this value indicates a better performance by a ratio of 10.2% compared with the closest solution.

GNSS user requirements for reuse development process considering pandemic

Global Navigation Satellite System (GNSS) use the internal continuous reference times to evaluate a navigation solution, which includes U.S. GPS time, Russian GLONASS Time, the E.U. Galileo System Time, and Chinese Beidou time. GNSSs time are designed and configured to internally synchronize systems and evaluate navigation solution, and they are adjusted to synchronize their time into an external and stable reference clock. This paper analyzes and extracts requirements that are needed for designing components and design a component specification, which is based on the extracted components. From this study, common functions of GPS applications were constructed as a component. This method has advantages that can be assembled and reused. That is, it would develop a highly reliable method for software when common components are extracted from requirements for GNSS construction and component-based GNSS development process is achieved.

GNSS Timing Performance Assessment and Results Analysis.

Global Navigation Satellite System (GNSS) timing is a main service function. Each GNSS has its own time performance specification. However, a uniform timing performance assessment methodology and its outcomes do not exist. Firstly, the timing performance specifications of each GNSS are analyzed. Then, time transfer accuracy is considered as the key GNSS timing performance indicator. Secondly, an assessment method for the Coordinated Universal Time (UTC) published by the Bureau International des Poids et Mesures (BIPM) and UTC kept by the National Time Service Center of China (UTC(NTSC)) is proposed. Thirdly, the uncertainty budget of the assessment method is given. The timing performances of BDS, GPS, GLONASS, and Galileo are assessed and compared. The results show that the time transfer accuracy of BDS, GPS, GLONASS, and Galileo was 13.8 ns, 4.5 ns, 16.8 ns, and 4.2 ns, respectively, in 2021, meeting their performance requirements specified by GNSS (30 ns or 40 ns). Meanwhile, the assessment results of GPS and Galileo are much better than requirements, while the assessment results of BDS and GLONASS show fixed time offset and can still be improved further. If the local reference time of GNSS users can be connected with UTC, this assessment method can be used.

Big data architecture and data mining analysis for market segment applications of differential global navigation satellite system (GNSS) services: case study of the analysis of the demand for navigation and agriculture

AbstractLocation and navigation services based on global navigation satellite systems (GNSS) are needed for real-time high-precision positioning applications in relevant economic sectors, such as precision agriculture, transport, civil engineering or mapping. Real-time navigation users of GNSS networks have significantly increased all around the world, since the 1990s, and usage has exceeded initial expectations. Therefore, if the evolution of GNSS network users is monitored, the dynamics of market segments can be studied. The implementation of this hypothesis requires the treatment of big volumes of navigation data over several years and the continuous monitoring of customers. This paper is focused on the management of massive connection of GNSS users in an efficient way, in order to obtain analysis and statistics. Big data architecture and data analyses based on data mining algorithms have been implemented as the best way to approach the hypothesis. Results demonstrate the dynamic of users of different market segments, the increasing demand over the years and, specifically, conclusions are obtained about the trends, year-on-year correlation and business volume recovering after economic crisis periods.

A Bidirectional Deep-Learning Algorithm to Forecast Regional Ionospheric TEC Maps

The rapid evolutions in Artificial Intelligence (AI) and the Machine Learning era have significantly improved accuracy for ionospheric space weather forecasting models. The ionospheric Total Electron Content (TEC) forecasting is necessary to alert Global Navigation Satellite System (GNSS) users about ionospheric space weather influences on satellite-receiver radio communications. Precise modeling and forecasting of the ionospheric TEC are critical for reliable and accurate GNSS applications. In this paper, a deep learning-based Bi-directional Long Short-Term Memory (Bi-LSTM) algorithm is implemented for 26 GPS (Global Positioning System) stations TEC data over the Indian region. The Bi-LSTM ionospheric TEC forecasting maps are generated and compared with ANN, and LSTM models during both geomagnetic quiet and disturbed periods. The potential of Bi-LSTM networks in time sequence processing is improved by having forward and backward connections. The Bi-LSTM results are demonstrated with and without solar and geomagnetic indices as input to the network. This work's outcome would help develop an ionospheric weather alert system for GNSS users.

A Novel GNSS Single-Frequency PPP Approach to Estimate the Ionospheric TEC and Satellite Pseudorange Observable-Specific Signal Bias

As the significant error sources influencing the Global Navigation Satellite System (GNSS) positioning, navigation, and timing (PNT) services, ionospheric delay and satellite hardware delay should be properly calibrated. Particularly, the pseudorange observable-specific signal bias (OSB) is convenient and can be directly corrected in the raw pseudorange measurement. In this work, we present a novel single-frequency ionospheric-free-half precise point positioning (PPP) (SFPPP2) approach for ionospheric studies, in which the ionospheric vertical total electron content (VTEC) and satellite OSB are isolated from the slant ionospheric observables by means of the ionospheric multilayer mapping function (MF). The computation and parameterization methods of the ionospheric VTEC and satellite pseudorange OSB are present. To validate the effectiveness and reliability of the novel method, we investigate and compare the performance of the single-frequency ionospheric-float PPP (SFPPP1), SFPPP2, and dual-frequency ionospheric-float PPP (DFPPP1) solutions for ionosphere sensing. The analytical results indicate that the novel approach can extract the slant ionospheric observables with the accuracy of submeters. The accuracy of the estimated ionospheric VTEC by the single-frequency PPP approaches is in the submeter level, which exhibits a slightly worse accuracy than that from the dual-frequency PPP solution. The estimated ionospheric VTEC accuracy is improved with the multilayer MF compared with the single-layer MF. The estimated BeiDou Navigation Satellite System (BDS) pseudorange OSB with the proposed SFPPP2 approach is stable, reliable, and of the high accuracy, and the rms’s with respect to Chinese Academy of Sciences (CAS) product for C2I and C6I signals with single-layer and multilayer MFs are 0.40, 0.41, 0.60, and 0.63 ns, respectively. The proposed PPP approach can retrieve the VTEC and satellite pseudorange OSB by mass-market receivers for the GNSS users.

GNSS User Technology: State-of-the-Art and Future Trends

Advances in the miniaturization, computational capabilities, and cost reduction of semiconductor technology have made global navigation satellite systems (GNSSs) the favorite choice for positioning. Currently, positioning is a key factor for many essential tasks in our modern society and will become even more important with the advent of new concepts such as the Internet of Things (IoT), smart cities and autonomous driving. The extensive use of GNSSs in a wide range of applications has caused their migration from the professional segment to the mass-market segment in terms of both technology and performance. This presents new and more stringent requirements in terms of accuracy, robustness, ubiquity, and continuity for the original “open sky” GNSS design. GNSS technology has experienced an unprecedented evolution in the last decade, and it is expected to exponentially evolve in the next decade. This evolution is considered in this paper with the aim of providing a unified reference for current GNSS receiver technologies and solutions and its expected evolution in the next decade. We consider receiver concepts, antennae, RF front ends, digital signal processing, and positioning algorithms. The impacts on the different GNSS market segments and applications are also analyzed.

Global Navigation Satellite Systems Spoofing Detection through measured Autocorrelation Function Shape Distortion

SummaryWith the expansion in Global Navigation Satellite System (GNSS) constellations and emerging applications utilizing GNSS systems, the issue of detection of interference is evolving as a growing concern in the satellite navigation user community. Threats for GNSS users can be classified as unintentional interference, jamming, and spoofing. Spoofing is more harmful among them because the target receiver might not be aware of the attack and, as a consequence, generate misleading position information. Spoofing attacks are classified as simplistic, intermediate, and sophisticated depending on their complexity of implementation. We focused primarily on the detection of intermediate spoofing attacks by measuring shape distortion (SD) through multiple correlators that cover multiple chips around the prompt tracking point. The SD metric compares the measured and typical values of the autocorrelation function and decides on the spoofing using a noise variance based threshold. The proposed SD metric is found to be very effective in detecting the spoofing attack during the pull‐off phase of the attack. The method is verified through simulations, synthetic spoofing data, and the TEXBAT data shared by the University of Texas, Austin. Different formulations of the proposed method are compared to provide an optimal number of correlator taps in each channel.