Assessment of positioning performances in Italy from GPS, BDS and GLONASS constellations

The use of multiple GNSS constellations has been beneficiary to positioning performances and reliability in recent times, especially in low cost mass-market setups. Along with GPS and GLONASS, GALILEO and BDS are the other two constellations aiming for global coverage. With ample research demonstrating the benefits of GALILEO in the European region, there has been a lack of study to demonstrate the performance of BDS in Europe, especially with mass-market GNSS receivers. This study makes a comparison of the performances between the combined GPS-GLONASS and GPS-BDS constellations in Europe with such receivers. Static open sky and kinematic urban environment tests are performed with two GNSS receivers as master and rover at short baselines and the RTK and double differenced post processed solutions are analyzed. The pros and cons of both the constellation choices is demonstrated in terms of fixed solution accuracies, percentage of false fixes, time to first fix for RTK and float solution accuracies for post processed measurements. Centimeter level accuracy is achieved in both constellations for static positioning with GPS-BDS combination having a slightly better performance in comparable conditions and smaller intervals. GPS-GLONASS performed slightly better for longer intervals due to the current inconsistent availability of BDS satellites. Even if the static tests have shown a better performance of GPS-BDS combination, the kinematic results show that there are no significant differences between the two tested configurations. Keywords: GNSS, BDS, GLONASS, NRTK positioning, Accurac

GNSS Shadow Matching: Improving Urban Positioning Accuracy Using a 3D City Model with Optimized Visibility Prediction Scoring

The poor performance of global navigation satellite systems (GNSS) user equipment in urban canyons is a well-known problem, especially in the cross-street direction. A new approach, shadow matching, has recently be proposed to improve the cross-street accuracy using GNSS, assisted by knowledge derived from 3D models of the buildings close to the user of navigation devices. In this work, four contributions have been made. Firstly, a new scoring scheme, a key element of the algorithm to weight candidate user locations, is proposed. The new scheme takes account of the effects of satellite signal diffraction and reflection by weighting the scores based on diffraction modelling and signal-to-noise ratio (SNR). Furthermore, an algorithm similar to k-nearest neighbours (k-NN) is developed to interpolate the position solution over an extensive grid. The process of generating this grid of building boundaries is also optimized. Finally, instead of just testing at two locations as in the earlier work, realworld GNSS data has been collected at 22 different locations in this work, providing a more comprehensive and statistical performance analysis of the new shadowmatching algorithm. In the experimental verification, the new scoring scheme improves the cross street accuracy with an average bias of 1.61 m, with a 9.4% reduction compared to the original SS22 scoring scheme. Similarly, the cross street RMS is 2.86 m, a reduction of 15.3%. Using the new scoring scheme, the success rate for determining the correct side of a street is 89.3%, 3.6% better than using the previous scoring scheme; the success rate of distinguishing the footpath from a traffic lane is 63.6% of the time, 6.8% better than using the previous scoring scheme

GPS-only, GLONASS-only and Combined GPS+GLONASS Absolute Positioning under Different Sky View Conditions

In recent years GNSS measurements techniques obtained a majority role in civil engineering and other technical fields. An example of this is the monitoring of both natural phenomena and manmade constructions. The main advantages of satellite positioning, as opposite to classical surveying techniques like levelling or total stations, are continuous long term observations and economic advantage, due to the lack of measurement crew. Currently, apart from GPS, other satellite systems in use like GLONASS or Galileo are becoming more important. Together with development of GNSS measurements for satellite positioning in open areas, also urban and mountainous areas can be measured. This kind of areas was excluded from measurements with single GNSS system, due to the lack of the required minimum number of visible satellites. Multi-GNSS (hybrid, integrated - usage of more than one satellite navigation system in measurements) positioning, currently providing more than 80 active satellites, opens new grounds for satellite measurements. Among measurement methods PPP is the most developing one since the beginning of 21st century. Main PPP advantages are: independence from reference station, lack of limitation of use to certain areas and global coverage with consistent, homogenous solutions. The paper shows the results of 90-days continuous static observations processed with the usage of PPP technique on simulated different sky view conditions. Measurements were made on points with known coordinates as a construction simulation. The data were processed in three modes: GPS-only, GLONASS-only and hybrid GNSS (GPS+GLONASS) using three different elevation cut-off angles. Accuracy analyses were carried out on the basis of final, daily EPN solutions at the observation time

Investigation of Shadow Matching for GNSS Positioning in Urban Canyons

All travel behavior of people in urban areas relies on knowing their position. Obtaining position has become increasingly easier thanks to the vast popularity of ‘smart’ mobile devices. The main and most accurate positioning technique used in these devices is global navigation satellite systems (GNSS). However, the poor performance of GNSS user equipment in urban canyons is a well-known problem and it is particularly inaccurate in the cross-street direction. The accuracy in this direction greatly affects many applications, including vehicle lane identification and high-accuracy pedestrian navigation. Shadow matching is a new technique that helps solve this problem by integrating GNSS constellation geometries and information derived from 3D models of buildings. This study brings the shadow matching principle from a simple mathematical model, through experimental proof of concept, system design and demonstration, algorithm redesign, comprehensive experimental tests, real-time demonstration and feasibility assessment, to a workable positioning solution. In this thesis, GNSS performance in urban canyons is numerically evaluated using 3D models. Then, a generic two-phase 6-step shadow matching system is proposed, implemented and tested against both geodetic and smartphone-grade GNSS receivers. A Bayesian technique-based shadow matching is proposed to account for NLOS and diffracted signal reception. A particle filter is designed to enable multi-epoch kinematic positioning. Finally, shadow matching is adapted and implemented as a mobile application (app), with feasibility assessment conducted. Results from the investigation confirm that conventional ranging-based GNSS is not adequate for reliable urban positioning. The designed shadow matching positioning system is demonstrated complementary to conventional GNSS in improving urban positioning accuracy. Each of the three generations of shadow matching algorithm is demonstrated to provide better positioning performance, supported by comprehensive experiments. In summary, shadow matching has been demonstrated to significantly improve urban positioning accuracy; it shows great potential to revolutionize urban positioning from street level to lane level, and possibly meter level

Određivanje fiksne točke mjerenja na mjestu događaja s pomoću jednoga GPS uređaja: utvrđivanje i minimiziranje pogrešaka na primjeru simuliranoga slučaja

The Global Positioning System (GPS) is a standard tool for establishing a datum point at the outdoor crime scenes that lack fixed objects or landmarks. However, GPS is prone to multiple errors that occur with a different intensity in different time intervals and degrade the accuracy of the positioning. In the present simulated case, we have examined the error of establishing a position using a single hand-held GPS unit, as well as the efficiency of reducing the error by averaging multiple coordinates collected at the same spot through the time. The results have shown great variations between the actual position and position obtained by GPS through collection time, demonstrating that a single GPS reading is not a reliable tool for establishing an accurate datum point in a forensic context. However, when a sufficient number of fixes is averaged, periodical variations of GPS error less affect accuracy, and error linearly decreases. To minimize the error of positioning in forensic cases, we suggest developing a model for GPS application that considers the acceptable degree of error, available equipment, the specificity of the crime scene location and defining a detailed workflow for reducing the error with the averaging method.Globalni položajni sustav (engl. Global Positioning System - GPS) standardno je sredstvo za određivanje fiksne točke mjerenja na vanjskim mjestima događaja na kojima nema fiksnih objekata i prepoznatljivih točaka. Ipak, GPS je osjetljiv na brojne pogreške koje se pojavljuju u različitim intenzitetima i u različitim vremenskim intervalima te nepovoljno utječu na točnost određivanja položaja. U izloženome slučaju, ispitana je pogreška određivanja položaja s pomoću jednoga GPS uređaja, kao i učinkovitost smanjenja pogreške s pomoću uprosječivanja većega broja koordinata prikupljenih na istoj točki u širemu vremenskom intervalu. Rezultati su pokazali znatne varijacije između stvarnoga položaja i položaja određenoga GPS-om tijekom razmatranoga vremena; što upućuje na to da jednostruko očitavanje GPS položaja nije prikladno za određivanje fiksne točke mjerenja u forenzičnome kontekstu. Međutim, kada se uprosječi određeni broj točaka prikupljenih na istome položaju – periodička kolebanja pogreške GPS-a manje utječu na točnost i pogreška linearno opada. Kako bi se pogreška utvrđivanja položaja svela na najmanju moguću mjeru, predlaže se razvijanje modela za primjenu GPS-a kojim bi se razmotrila prihvatljiva razina pogreške, dostupna oprema i posebnosti različitih mjesta događaja te potanko odredio način i tijek smanjenja pogreške metodom uprosječivanja

Određivanje fiksne točke mjerenja na mjestu događaja s pomoću jednoga GPS uređaja: utvrđivanje i minimiziranje pogrešaka na primjeru simuliranoga slučaja

The Global Positioning System (GPS) is a standard tool for establishing a datum point at the outdoor crime scenes that lack fixed objects or landmarks. However, GPS is prone to multiple errors that occur with a different intensity in different time intervals and degrade the accuracy of the positioning. In the present simulated case, we have examined the error of establishing a position using a single hand-held GPS unit, as well as the efficiency of reducing the error by averaging multiple coordinates collected at the same spot through the time. The results have shown great variations between the actual position and position obtained by GPS through collection time, demonstrating that a single GPS reading is not a reliable tool for establishing an accurate datum point in a forensic context. However, when a sufficient number of fixes is averaged, periodical variations of GPS error less affect accuracy, and error linearly decreases. To minimize the error of positioning in forensic cases, we suggest developing a model for GPS application that considers the acceptable degree of error, available equipment, the specificity of the crime scene location and defining a detailed workflow for reducing the error with the averaging method.Globalni položajni sustav (engl. Global Positioning System - GPS) standardno je sredstvo za određivanje fiksne točke mjerenja na vanjskim mjestima događaja na kojima nema fiksnih objekata i prepoznatljivih točaka. Ipak, GPS je osjetljiv na brojne pogreške koje se pojavljuju u različitim intenzitetima i u različitim vremenskim intervalima te nepovoljno utječu na točnost određivanja položaja. U izloženome slučaju, ispitana je pogreška određivanja položaja s pomoću jednoga GPS uređaja, kao i učinkovitost smanjenja pogreške s pomoću uprosječivanja većega broja koordinata prikupljenih na istoj točki u širemu vremenskom intervalu. Rezultati su pokazali znatne varijacije između stvarnoga položaja i položaja određenoga GPS-om tijekom razmatranoga vremena; što upućuje na to da jednostruko očitavanje GPS položaja nije prikladno za određivanje fiksne točke mjerenja u forenzičnome kontekstu. Međutim, kada se uprosječi određeni broj točaka prikupljenih na istome položaju – periodička kolebanja pogreške GPS-a manje utječu na točnost i pogreška linearno opada. Kako bi se pogreška utvrđivanja položaja svela na najmanju moguću mjeru, predlaže se razvijanje modela za primjenu GPS-a kojim bi se razmotrila prihvatljiva razina pogreške, dostupna oprema i posebnosti različitih mjesta događaja te potanko odredio način i tijek smanjenja pogreške metodom uprosječivanja

Navigation Recommender:Real-Time iGNSS QoS Prediction for Navigation Services

Global Navigation Satellite Systems (GNSSs), especially Global Positioning System (GPS), have become commonplace in mobile devices and are the most preferred geo-positioning sensors for many location-based applications. Besides GPS, other GNSSs under development or deployment are GLONASS, Galileo, and Compass. These four GNSSs are planned to be integrated in the near future. It is anticipated that integrated GNSSs (iGNSSs) will improve the overall satellite-based geo-positioning performance. However, one major shortcoming of any GNSS and iGNSSs is Quality of Service (QoS) degradation due to signal blockage and attenuation by the surrounding environments, particularly in obstructed areas. GNSS QoS uncertainty is the root cause of positioning ambiguity, poor localization performance, application freeze, and incorrect guidance in navigation applications. In this research, a methodology, called iGNSS QoS prediction, that can provide GNSS QoS on desired and prospective routes is developed. Six iGNSS QoS parameters suitable for navigation are defined: visibility, availability, accuracy, continuity, reliability, and flexibility. The iGNSS QoS prediction methodology, which includes a set of algorithms, encompasses four modules: segment sampling, point-based iGNSS QoS prediction, tracking-based iGNSS QoS prediction, and iGNSS QoS segmentation. Given that iGNSS QoS prediction is data- and compute-intensive and navigation applications require real-time solutions, an efficient satellite selection algorithm is developed and distributed computing platforms, mainly grids and clouds, for achieving real-time performance are explored. The proposed methodology is unique in several respects: it specifically addresses the iGNSS positioning requirements of navigation systems/services; it provides a new means for route choices and routing in navigation systems/services; it is suitable for different modes of travel such as driving and walking; it takes high-resolution 3D data into account for GNSS positioning; and it is based on efficient algorithms and can utilize high-performance and scalable computing platforms such as grids and clouds to provide real-time solutions. A number of experiments were conducted to evaluate the developed methodology and the algorithms using real field test data (GPS coordinates). The experimental results show that the methodology can predict iGNSS QoS in various areas, especially in problematic areas

GNSS shadow matching: Improving urban positioning accuracy using a 3d city model with optimized visibility scoring scheme

Global navigation satellite system (GNSS) positioning is widely used in land vehicle and pedestrian navigation systems. Nevertheless, in urban canyons GNSS remains inaccurate due to building blockages and reflections, especially in the cross-street direction. Shadow matching is a new technique, recently proposed for improving the cross-street positioning accuracy using a 3D model of the nearby buildings. This paper presents a number of advances in the shadow-matching algorithm. First, a positioning algorithm has been developed, interpolating between the top-scoring candidate positions. Furthermore, a new scoring scheme has been developed that accounts for signal diffraction and reflection. Finally, the efficiency of the process used to generate the grid of building boundaries used for predicting satellite visibility has been improved. Real-world GNSS data has been collected at 22 different locations in central London to provide the first comprehensive and statistical performance analysis of shadow matching. © 2013 Institute of Navigation

GNSS Vulnerabilities and Existing Solutions:A Review of the Literature

This literature review paper focuses on existing vulnerabilities associated with global navigation satellite systems (GNSSs). With respect to the civilian/non encrypted GNSSs, they are employed for proving positioning, navigation and timing (PNT) solutions across a wide range of industries. Some of these include electric power grids, stock exchange systems, cellular communications, agriculture, unmanned aerial systems and intelligent transportation systems. In this survey paper, physical degradations, existing threats and solutions adopted in academia and industry are presented. In regards to GNSS threats, jamming and spoofing attacks as well as detection techniques adopted in the literature are surveyed and summarized. Also discussed are multipath propagation in GNSS and non line-of-sight (NLoS) detection techniques. The review also identifies and discusses open research areas and techniques which can be investigated for the purpose of enhancing the robustness of GNSS