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L'article présente le projet ERSAT GGC et les techniques de détection des effets locaux sur les GNSS développées pour l'introduction du GNSS dans le système ERTMS/ETCS

In this paper we present a modular framework to classify railway track areas regarding the expected presence of local GNSS threats. This information might be critical for a safe signalling operation, for example to determine where virtual balises could be placed safely. We show first how different GNSS threats can be detected using dedicated detection algorithms and how these individual detection results can be then transformed from time to the track domain. An overall decision logic is subsequently used to identify an area as suitable or unsuitable for GNSS usage by combining all available GNSS data collected over the same track area. Finally, the framework implementation is evaluated with railway data obtained during a measurement campaign in Sardinia, Italy in 2019. Even though developed in the railway context, the presented framework architecture and methodology may be also considered to perform similar classification tasks for other means of transport.

Satellite navigation plays a critical role in new railway signaling and train control systems. It will allow higher levels of automation at a reduce cost in installation and maintenance as compared to current infrastructure-based technologies. However, in order to be integrated in railway systems, GNSS must guarantee the stringent railway safety requirements. GNSS safety has been extensively quantified for the aviation community, however, in the railway environment the probability of local GNSS hazards like interferences is larger due to its operation in a non-restricted space. Railway GNSS receivers must be therefore equipped with mechanisms to protect the position determination from being corrupted by undesired interferences (jamming or spoofing) without being aware of it. In this paper and based on Commercial-Off-The-Shelf (COTS) hardware we implemented interference detection functions suitable for railway localization. We detail the algorithm design as well as the necessary calibration procedure to determine the nominal signal model. The performance of the interference detection is analyzed with an experimental setup on a commercial train during the measurement campaign organized for the EU project ERSAT-GGC. Figures about the detection capability and detected events along the selected line are finally provided.

This deliverable is the second report delivered by GATE4Rail WP3. The general objective of WP3 was to define a comprehensive methodology and the associated tools able to characterise the Global Navigation Satellite System (GNSS) performance into the railways application scenarios defined in WP2 in the framework of a VB detection in ERTMS (European Railway Traffic Management System)/ETCS (European Train Control System) context.The work performed in WP3 is focused on the definition of the main railway environments that will impact GNSS reception, thus PVT performance. This deliverable D3.2 in particular, defines which are the key hazards (both local and global) that have to be taken into account and simulated in order to cover the main events that can occur during a railway operational scenario and how error models will be introduced in the simulation framework defined by the project.

Before deployment and commissioning of new positioning products/applications, manufacturers need to perform long and often expensive field trials in targeted operational environments in order to assess and certify future behaviour. The community trust on GNSS (Global Navigation Satellite System) is so high that more and more safety critical applications based on satellite navigation are under development. With the increase of criticality level of GNSS applications, a relevant means to predict the performances and reliability of future applications is needed. Thus in this paper we introduce a new architecture based on Machine Learning that combines classical observables for local hazard detection, with the outcome of advanced RAIM in order to determine whether a given point of a railway is suitable for a safe and reliable use of GNSS for train positioning.

In the last years, several studies have addressed the introduction of the GNSS technology in the framework of the high integrity positioning methods for the land transportation. The main emphasis has been spent for the rail environment. The main driver is the possibility to realize cost effective solution for the modernization of the lines without losses in terms of safety. Furthermore, the rail community have recognized GNSS as one of the step charge innovation foreseen in the next generation train control systems. In the recent period, there has been some attempts to exploit the outcome of such studies even in the driverless car applications. As a matter of fact, these two transportation means share the same electromagnetical environment and both of them are subjected to constrained movement profile. Since one of the most important KI in the safety related application is represented by the integrity, we considered the presence of an external augmentation and integrity monitoring network. Particularly, we considered three different approaches for augmenting the PVT solution that are respectively the local area augmentation network, the wide area augmentation network and the 2-tiers augmentation schemes. For all these schemes we carried out the SWOT analysis considering the peculiarities of the application. On the basis of the SWOT, the system integrator can decide to implement the network that better suit its own requirement. In or vision, the best solution is to share a unique augmentation network for both rail and connected cars. In this way it is possible to increase the number of user served by the network itself.

This document is the deliverable D4.2-Technical Specification of the Survey Toolset where the outcome of the work performed in WP4.2 of the ERSAT GGC project is described. This document follows up the work performed in WP4.1 and reported in the deliverable D4.1, extending the ongoing general definition of the track area classification process. The goal of WP4.2 is the specification and development of the toolset for the survey and classification of track areas, giving the system overview and providing the different interacting blocks as the measurement hardware system, the processing software toolbox and the final classification data. Regarding this D4.2, the functional and technical specifications of the toolset are here provided with the description of the interfaces between the different detection techniques and decision logic blocks. Outcome of D4.3 will be the prototype implementation and installation. The document also includes the specification of the measurement system and hardware to be used in the survey process so that the necessary data for the classification techniques can be collected in the railway scenario. Finally, the specification of the output data - the track area classification results - is also analysed and provided. The specification of the survey measurement system and software toolset addressed in the current document will support the next project activities related to the development of the software tools for the classification of track areas in WP4.2 and the execution of measurement campaigns in WP4.3.

This document is the deliverable D4.3-Prototype Implementation of the Survey Toolset, which provides a high level description of the Toolset Prototype. This document is released in a pre-final version, where the toolset implementation has been done using demo data coming from RFI-ASTS private campaign in Italy. The dataset, related to the Pinerolo-Torino line, was used to test and debug the toolset, and the results provided in this document refer to that line and campaign. The Consortium thanks RFI, ASTS and TRI for the investment done to this aim and the availability of needed dataset in order to respect the scheduling of the project. The toolset will be definitively designed after the test campaigns on field, which will confirm the assumptions and in particular the decision logic approach. In fact, once the test campaigns foreseen in the ERSAT GGC will be performed - as planned in the WP4.3 task - the final implementation of the toolset prototype will be released based on those data. A conclusive issue of this deliverable will be then provided with the results of the test campaigns.

This document reports the execution of the track area classification process developed during the work package « WP4 Track Survey and Track Classification » along with the main outcomes and results obtained during this process. The goal of WP4 is to set up a standard measurement and classification system that is able to provide a prediction of the expected presence of GNSS hazard causes and degraded performance to be expected at a given track area, in order to enable the evaluation if the specific environment is suitable or not to place virtual balises or on the contrary should be discarded beforehand. In this document, we detail the results of applying the classification standard process, by means of the developed software Toolset to the measurement data collected in the three measurements campaigns during ERSAT GGC project. This execution report addressed the main important aspects that need to be carried out for the correct application of the classification process and the results obtained with the data collected.

ITST 2018, 16th International Conference on Intelligent Transport Systems Telecommunications, Lisbonne, PORTUGAL, 15-/10/2018 - 17/10/2018; The introduction of the GNSS positioning technology into the evolution of ERTMS/ETCS is based on the concept of virtual balise to minimize the impact onto existing ERTMS solutions. The detection of virtual balises is foreseen by using GNSS in combination with odometry information. However, the presence of local GNSS threats (e.g, multipath, NLOS or interference) may lead to unbounded errors in the pseudorange measurement that cannot be corrected by local or wide-area augmentation systems, and will lead ultimately to an error in the virtual balise position that cannot be bounded with the required integrity. In order to a priori prevent the risk of this hazardous situation, virtual balises must be logically located in areas where there are not local threats that may lead a Virtual Balise Transmission System on board the train to dynamically estimate unbounded virtual balise position errors. This paper summarizes the initial work performed in the H2020 GSA Project ERSAT-GGC with respect to the different techniques that can be used to detect local GNSS threats and that can support a later classification of railway areas as suitable or not suitable for placing virtual balises.

Autonomous driving technology requires high accuracy and high integrity position and navigation. No individual technology can currently meet these requirements anywhere, anytime and under any condition. Sensor fusion is considered as the go-to-solution for the development of fully autonomous driving technology. GNSS is an element of a sensor fusion based navigation system that includes lidars/radars, inertial sensors and cameras. This work shows as the comparison between the speed’s vehicle calculated by odometer and one estimated by GNSS receiver installed on board of train through Doppler is an effective means to face multipath in railway environment, even when just one receiver is available. Moreover, the georeferenced knowledge of the railway is not essential when Doppler are compared, while the pseudorange comparison requires a guess of the baseline between the receivers. Moreover, the proposed multipath detection and exclusion method is fully compatible with other techniques for multipath mitigation. The outcomes of this work, undertaken for railway scenarios, can be partly exploited in driver-less car applications thanks to the analogies between these two transportation sectors.

The deliverable D4.1 Procedure Specification Document of the ERSAT-GGC project is related to the work performed in Task 4.1. The aim of WP4 is to set up a standard measured system that is able to provide a forecast method for the GNSS service performance to be expected at a given track point, in order to enable evaluation whether the specific scenario is favourable to place virtual balises or on the contrary should be discarded beforehand. The results of this assessment can be included in a database map where geo-referenced GNSS quality data is stored. Users may access the information via specified interfaces using standardized communication channels. In order to set up the system, at first a standardized process has to be defined and specified that will determine what has to be measured under which conditions and what has to be simulated for GNSS characterizing along the line. This is the scope of Task 4.1. In order to set the context of the work, a description of the need and importance of a standard process to classify the track areas for virtual balise placement is given in the introduction. Later, a first version of the high level requirements to the classification process is provided. Based on these requirements a preliminary study of the different techniques, measurements and parameters that are relevant to define a safe track area classification standard process has been performed. The document then focus on a detail description on the GNSS detection techniques that are relevant for the standard process and the track area classification criteria. Further works related to the detection and classification criteria are required, and they will be included in the next deliverable D4.2, which specifies the dedicated requirements for the toolset.The standard process will undergo reviews until the execution and test: all these improvements and the related links to the toolset development will be covered by the next deliverables of WP4.

The work deals with introduction of GNSS (Global Navigation Satellite System) technology into the railway sector. Particularly, since the requirements imposed by the railway environment are stringent, the use of an external mean for providing integrity monitoring and augmentation is highly recommended. In this paper, we show an algorithm based on GNSS code double differences to identify and exclude multiple satellite faults by using data acquired by multiple reference stations. The simulations results carried out in this framework are presented in terms of detection probability and false alarm rate.

The adoption of the GNSS for the European Rail Train Management System – ERTMS is one of the objectives included into the ERTMS evolution plan to improve its competitiveness on the market. To this aim, in 2015 the European Global Navigation Satellite System Agency (GSA) approved the “ERTMS on SATELLITE –Enabling Application Validation (ERSAT–EAV)”, project with the object to verify the suitability of GNSS to generate Virtual Balises as an alternative/complement means to the physical balises prescribed by the ERTMS. The architecture of ERSAT EAV – based on joint use of multiple constellations and public augmentation networks - would be a contribution to foster cost-effective ERTMS solutions, primarily for the local and regional lines in Europe for which the economical sustainability is a priority. The paper describes the hazard’s mitigation techniques affecting the on board GNSS receiver when operating in harsh environments, and the scenarios for a smooth introduction of GNSS into the ERTMS system. Field test results carried out on a Test Bed implemented on a 50km line in Sardinia are presented and discussed.

The evolution plan of the European Railways Train Management System (ERTMS) includes the GNSS localization as one of the Game Changer technologies to improve the competitiveness of the ERTMS. GNSS will allow the implementation of cost-effective solutions to reduce the maintenance and operational cost without reducing the safety levels required by railway operations. The inherent low power of satellite navigation signals exposes GNSS-based solution to Radio Frequency threats, namely intentional or unintentional interference, that can lead to performance degradation or denial of service, and to spoofing/meaconing attacks, that can lead to receiver deception and hence to misleading PVT (Position, Velocity and Time) estimation. The aim of this paper is to present an architecture for detection and mitigation of radio-frequency hazards in a rail operational environment. The investigated solution is based on a Digital Beamforming Platform (DBP) coupled with advanced GNSS signal processing techniques for high rejection of GNSS interfering and counterfeit signals. This approach fully exploits the characteristics of the railway context, to support the evolution of the Location Determination System (LDS) based on GNSS in ERTMS Train Control System (TCS). This paper presents the DBP architectural design, focusing on the most meaningful and innovative solution foreseen for the prototype implementation. Each subsystem of the DBP is described in details, and a preliminary assessment of the performances is provided, by means of simulative and analytic tools.

This paper proposes a local augmentation and integrity monitoring network for railway and shows the obtained performances in terms of accuracy positioning in case of satellite faults. The simulations results show that the system can detect and discard tha faulty satellite, still mantaining the accuracy on positioning accetable. The work is inserted in the scenario of introduction and application of space technologies based on the ERTMS (European Railways Train Management System) architecture. It foresees to include the EGNOS-Galileo infrastructures in the train control system, with the aim at improving performance, enhancing safety and reducing the investments on the railways circuitry and its maintenance. © 2014 IEEE.

In the frame of GATE4Rail project, Work Package (WP) 3 deals with the definition of a comprehensive methodology and the associated tools able to characterise the GNSS performance into the railways application scenarios defined in WP2 in the framework of a Virtual Balise detection in ETCS/ERTMS context. The present document (deliverable D3.1) is the first report delivered by GATE4Rail WP3. It is specifically dedicated to the definition of a standardised database in order to characterize GNSS in different rail scenarios and the description of Consortium tools included in the GATE4Rail test-bed able to generate local and global hazards and evaluate their impact on GNSS performance