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GNSS are widely used in localization applications. These systems have the advantage of being able to locate, at low-cost, receivers anywhere on the planet's surface without prior knowledge of the position. However, the accuracy of the provided position strongly depends on the quality of reception and on the number of signals received. And these depend on the environment around the receiver. Indeed, certain environments such as urban canyons or forests are known to be challenging because multiple phenomena such as multipath, Non-Light Of Sight (NLOS), or interference are common there. These phenomena induce an erroneous estimate of the position. In applications where the localization function does not constitute a critical function involving the safety of the overall system, this erroneous estimate only constitutes an inconvenience. But in applications for which the safety of goods or people is at stake, the tolerance of what is called the integrity risk is infinitesimal, not to say null. Moreover, in this type of application, it is not so much the position that matters but the ability to limit the unknown position error. For that, the literature proposes different possibilities of protection level calculation. The ideal protection level would be the one that limits the unknown error as closely as possible without ever underestimating it. This makes it possible to minimize hazardous operations as well as unavailability of the localization function. In this paper, we are interested in the impact of GNSS observation weighting models on the protection levels. We propose a model capable of carrying a multi-criteria and multi-parametric strategy allowing a better adaptivity to the navigation context. The encouraging experimental results show that a parametric and constrained modelling strategy of errors, from the design step, relaxes the requirements on the calculation of the protection levels. They also show the complementarity between the characterization of errors which must be concerned with the functional behaviour and a Fault Detection and Exclusion layer which is responsible for the dysfunctional behaviour.

ION ITM 2021 - International Technical Meeting of Institute of Navigation, Virtual, , 25-/01/2021 - 28/01/2021; The accuracy of the satellite-based positioning system is severely affected in the presence of local phenomenons like multipath, NLOS and interferences. These local effects are difficult to model due to spatial and (or) temporal dependencies. This study aims to model the position error on the track and later use it for the track classification. The characterization of the track errors can be beneficial as it can help to increase the capacity of the railway track by providing adaptable protection level and also for sending warning alerts to the other trains if any of them is in degraded mode to avoid any sort of accidents. We present a very simple machine learning approach to model the position error. For this purpose, we investigate the Expectation-Maximization (EM) algorithm to estimate the parameters of the Gaussian Mixture Model (GMM). We intuitively selected 3 classes to represent different error shape features to avoid complexity and to keep some diversity. In the learning phase, 5 different runs are used to capture as much as the error variations on the track throughout the day. The models estimated in the learning process is applied to the test samples for the track characterization. The results show that class representation varies due to the error variation within the day. For some particular obstacles, the track is always represented by the class that shows deteriorated conditions. It also shows that the class representation is very similar to the learning samples when the error models are applied to the test sample collected on a different day with a nearly similar satellite configuration.

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

ENC 2020, 28th European Navigation Conference, Dresden , ALLEMAGNE, 23-/11/2020 - 24/11/2020; The work shows the high level concept and methodology followed for designing a geo-distributed simulation and verification infrastructure connecting remotely GNSS excellence centres and ERTMS/ETCS laboratories to evaluate the GNSS performances in the railway environment. Proper methodology and tools are adopted to simulate GNSS behaviour in different railway scenarios in nominal or in presence of global and local hazards. Particularly, the test-bed main goals are: i) achieving a realistic characterization of the environment in terms of railway and GNSS infrastructures able to evaluate the performances and properties of some fail-safe train positioning components in nominal and fault conditions; ii) defining a common test process framework for zero on-site testing instead of testing on-site saving effort and time. The test-bed offers the unique advantage to stress the global system in presence of very rare GNSS fault events instead of performing long and expensive measurement campaigns on field for detecting them and analysing their impact on ETCS. The work will show its description and the methodology adopted for its design and implementation.

ENC 2020, 28th European Navigation Conference, Dresden , ALLEMAGNE, 22-/11/2020 - 25/11/2020; GNSS observations weighting models have received attention in the past decades. Several reasons can explain this gain in consideration. It mainly corresponds to the emergence of autonomous, global, continuous, precise and integrity-compliant localization systems. Indeed, for safety critical applications, adopting a naive strategy of observations' equal weighting could not guarantee to achieve all goals, and even more for terrestrial applications where the local environment can strongly disturb signals reception. The existing observation models use one or two metrics to estimate the confidence to be given to an observation. The first is the satellites' elevations. This model considers that the satellites with low elevation are more subject to global errors (orbit and atmosphere errors) or local multipaths or NLOS phenomena. The second criterion is the carrier to noise ratio provided by the receiver. However, combining these two criteria by a simple multiplication of the two models taken separately, presents a limit: the result is no more « under control ». In this study, we propose to formulate a new weighting strategy using these two criteria more guided by expertise's expected results.

The work shows the high level concept and methodology followed for designinga geo-distributed simulation and verification infrastructure connecting remotely GNSSexcellence centres and ERTMS/ETCS laboratories to evaluate the GNSS performances in the railway environment. Proper methodology and tools are adopted to simulate GNSSbehaviour in different railway scenarios in nominal or in presence of global and localhazards. Particularly, the test-bed main goals are: i) achieving a realistic characterization of theenvironment in terms of railway and GNSS infrastructures able to evaluate theperformances and properties of some fail-safe train positioning components in nominal and fault conditions; ii) defining a common test process framework for zero on-sitetesting instead of testing on-site saving effort and time. The test-bed offers the unique advantage to stress the global system in presence of veryrare GNSS fault events instead of performing long and expensive measurementcampaigns on field for detecting them and analysing their impact on ETCS. The work will show its description and the methodology adopted for its design and implementation. &nbsp

ION ITM 2020, International Technical Meeting of Institute of Navigation, San Diego, ETATS-UNIS, 21-/01/2020 - 24/01/2020; GNSS used as a standalone positioning system fulfils most of the requirements for many applications since decades. However, the need of high available, accurate and fail-safe positioning systems for new applications such as rail autonomous vehicles for train signaling applications motivates the community to explore novel solutions. In this context, multi-constellation multi-frequency GNSS receivers have the potential to enhance the positioning solutions. However, when applied to safety-critical land transportation system, the localization function not only needs to meet accuracy requirements, but more importantly, it also needs to bound the positioning errors in order to reduce the risk of unexpected and undetected faults. Thus, in order to reach continuous and fail-safe positioning solutions, the use of complementary heterogeneous sensors with a smart hybridization becomes essential. For safety-related and regulated applications as in railways, one will also need, as a next step, to develop the capacity of assessing the safety of the hybrid solution. The concept of integrity can help to reach this requirement and is currently investigated for rail applications. RAIM (Receiver Autonomous Integrity Monitoring) was first defined for aviation applications and is widely used for their safety assessment. However, due to the different safety requirements and operational environment in aviation and land applications (i.e. railway and road application), dedicated algorithms need to be developed for such applications. Indeed, terrestrial applications can face particularly harsh environments (urban canyon, forests ...) in which a dilemma appears between the (reduced) availability of visible satellites and the possibility of encountering multiple simultaneous errors (NLOS, multipath interferences ...). Under these conditions, implementing a strategy based solely on a FDE layer can lead to a decrease in the availability of the localization function. Conversely, relying solely on a strategy of weighting observation error models cannot constitute an acceptable solution from a safety point of view. Only a harmonious combination of these two strategies in a stringent environmental condition can achieve the availability and security requirements. With a real dataset collected along a railway line, we compare the positioning accuracy of a GNSS/IMU tightly coupled system before and after weighting and FDE schemes. The results show that the average value of Horizontal Position Error (HPE) has been reduced after applying the performance improvement method on the GNSS/IMU system. It also shows that the implemented Horizontal Protection Level (HPL) correctly bounds HPE.

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.

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.

Global Navigation Satellite Systems (GNSS) have continually involved in our daily life in the past decades. Among all these GNSS-based applications, there is an increasing number of GNSS-based urban transport applications, especially the critical liability ones, such as the Electronic Toll Collection (ETC) and the Intelligent Transport System (ITS). For these GNSS-based applications, not only positioning accuracy but also its reliability is required. Latter has attracted more and more attention from urban GNSS users. Yet urban environments present great challenges for common commercial GNSS receivers since the existence of local effects such as multipath and the Non-Line-of-Sight (NLOS) receptions. The main objective of this paper is to investigate the integrity performance one can expect from a low-cost common GNSS receiver. Under this framework, this paper proposes an innovation-based integrity monitoring scheme by using an Extended Kalman Filter (EKF) with the help of carrier-power-to-noise ratio $(C/N_{0})$ weighting. The derivations of the Horizontal Protection Level (HPL) for the EKF innovation-based integrity monitoring is also presented in detail. The accuracy and integrity performances are evaluated with real GPS data collected in urban environments. Compared to the classic residual-based snapshot Receiver Autonomous Integrity Monitoring (RAIM), the innovation-based EKF integrity monitoring scheme presents more advantages in terms of accuracy and integrity. With the real dataset collected in urban canyon of Nantes center, the results show that the average size of horizontal position error has been reduced by 1.15 meter with the proposed approach compared to the classic weighted RAIM, the median size of HPL has been reduced by 7.5 meters and the algorithm availability is 100% instead of 98.57 %.

ION 2018, PPTI - Precise Time and Time Interval Meeting, Reston, ETATS-UNIS, 29-/01/2018 - 01/02/2018; Train location is of main use in railway signaling applications, today with the help of equipment on tracks. This equipment's role is to detect the train presence on a track section. In the European standard ERTMS/ETCS (European Rail Traffic Management System/European Train Control System) for the signaling, control and train protection this is performed thanks to a balise or a group of balises installed on tracks to give a passing train a position reference. The balise initializes the odometer, and the train position is computed by the odometer as a distance run since the last relevant balise group. In level 3 of ETCS, the train location shall be sent by the train itself to the ground. It will allow reducing the number of trackside equipment on the one hand, and on the other hand allow implementing moving block circulation in order to reduce the train spacing thus improve line capacity. Mainly driven by economic reasons and thus, acceleration of ERTMS penetration into the networks, the use of GNSS-based systems and, in particular, their introduction in signaling systems is seriously investigated today as a positioning opportunity included in ETCS and tested all around the world. Most of the past projects focused on the development of localization unit and their performance evaluation or more globally on the demonstration of operational signaling solutions based on a GNSS-receiver. As the suitability will be strongly linked to local GNSS quality determination, impact of multipath, signal attenuation or obstruction, one of the objectives of the EU ERSAT GGC project will deal with the development of a methodology and toolsets for classifying track areas. A video-based tool will be used in order to characterize the reception environment of the GNSS signals along real lines with a limited time of experimentation.The paper presents the project and how the tool will be used in it.

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 use of global navigation satellite systems (GNSS) will provide significant advantages for ensuring the control of train movements on railway networks equipped with European Rail Traffic Management System/European Train Control System (ERTMS/ETCS). Indeed, this disruptive technology can play an important role for reducing the rail infrastructure's equipment by enabling trains to determine their position in an autonomous way. Specific associated hazards have to be considered in the European signaling system. From this perspective, performances of GNSS-based localization systems were analyzed in different past studies. They highlighted what they can bring to the railway domain. For going further than performance-centric analyses to help inserting these systems safely in rail applications, this paper want also to focus on their operating uses. For that, the safety evaluation proposed in this paper is able to handle specific estimated confidence-related data that are associated to an estimated position. This paper first details the managed risks in ETCS due to the localization function with, in particular, those that may arise due to GNSS-based systems. It discusses the evolution of these risks when dealing with moving block operation of the ETCS-level 3. The safety evaluation approach is then explained. It relies in fact on extended integrity data handled in the case of the train spacing. Finally, it is applied in different operational cases to show evaluation results when real GNSS data are measured in a railway environment.

Integrity is one of the most important parameters characterizing the Global Navigation Satellite Systems (GNSS) performance for safety-related applications. It is defined as a measure of trust to be placed in the correctness of the information supplied by the total system. This concept is more and more important, especially for applications in urban environment with standalone GNSS system, where GNSS performance is strongly degraded by the signal propagation conditions. Non line of Sight (NLOS) signals, caused by the surrounding obstacles, are of particular interest, as the error they induced remains a large cause of inaccuracy. In order to get rid of these constraints and to guarantee a better performance of positioning accuracy as well as integrity, several approaches can be used, such as positioning weighting models, 3D city models, Fault Detection and Exclusion (FDE) techniques etc. Since the concepts of integrity and accuracy are strongly related to each other, the main objectives of this paper are to reduce and to bound position errors in order to pave the way for further work of integrity. In the work presented here, we will introduce 2 classes of methods which contribute to the NLOS signal mitigation as well as integrity performance. The first class concerns the use of different weighting models in order to reduce the influence of the NLOS on the overall measurements. The second class consists of Fault Detection and Exclusion (FDE) algorithms which allow users to identify and remove the outliers. Using the real GPS data collected from an experiment in Nantes, firstly, we compare the Ordinary Least Square (OLS) and the Weighted Least Square (WLS) solutions with four different weighting models whose variances depend respectively on: 1) Dirichlet Process Mixture (DPM) [1], 2) the Carrier-to-Noise Ratio C/N0 [2], 3) the satellite elevation [3], 4) the hybridization of the C/N0, the satellite elevation and an indicator of LOS/NLOS signal [4], which comes from an “urban trench” model [5]. The simulation results prove that the hybridized weighting model can achieve a significant improvement in terms of accuracy compared to the other three models: the 95% horizontal position accuracy can be improved by about 78.39%. Then, with the same data and the DPM weighting model as the basic position estimation algorithm, four FDE algorithms are respectively implemented: 1) Subset testing 2) Global and sequential local test 3) Forward Back testing [6] 4) Danish method [6][7]. The simulation results show that the position accuracy can also be well improved with FDE algorithms since unreliable positioning caused by large errors can be excluded. Thus, integrity performance can be better guaranteed but system availability is inevitably reduced.