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Highlights: [•] We enhance GNSS accuracy in urban environments. [•] We have developed satellite state of reception detection with an image processing strategy. [•] Image processing sky detection with GNSS data selection improves positioning accuracy. [•] Experimental results illustrate performances by comparison with a ground truth. [ABSTRACT FROM AUTHOR]

Abstract: Satellite-based localization technologies are strategic opportunities in railway applications because they offer new possibilities of service and have advantages that current technologies relying mainly on infrastructures deployed along tracks cannot equal. GNSSs (Global Navigation Satellite Systems) can, in particular, offer localization services in ERTMS (European Rail Traffic Management System), the system developed within the European railway community to harmonize, at European scale, railway signalling and control/command systems. However, using GNSS in such safety applications is slowed down when trying to comply with railway standards. Indeed, demonstrations of RAMS properties (Reliability, Availability, Maintainability, Safety) are required on new solutions embedded in trains. They aim at verifying if all dependability (RAM) and safety aspects are controlled over the lifecycle of the solutions before using them operationally. No RAMS evaluation technique exists for systems based on signal propagation and subject to failures provoked by environment effects. The major challenge is so to develop proof methods that will give means to fulfil the railway certification process. In this article, we propose a procedure to work in that direction after having presented the advantages, the possibilities and the challenges to use GNSS in rail transportation. The procedure is based on experiments for the evaluation of RAMS properties related to satellite-based localization units. We apply the method to different position measurements obtained in several typical railway environments. The obtained results are discussed according to the dependability and safety points of view. [Copyright &y& Elsevier]

Applications of global navigation satellite system (GNSS) in land transportation systems are already extensively deployed and will certainly continue to grow especially in the framework of intelligent transport systems. However, one of the best-known drawbacks of such a system is the lack of satellite visibility in dense urban areas as well as in some specific embedded railway environments. This restricts considerably GNSS use for extended safety related applications. In this paper, a new tool is proposed to predict the availability of a satellite constellation from the point of view of the land transportation user. Knowing the trajectory of a land vehicle, the tool predicts the number of satellites that will be received and produces a safety criterion able to qualify the GNSS localization result. A first version of the tool, already in operation, merges an image processing approach providing the knowledge of the land environment, and the output of a satellite tracking program predicting satellite positions in the sky. This allows us to determine, using a simple optical approach, the number of satellites received in line-of-sight or blocked, with regard to the nearby environment of the receiving antenna. Results obtained in railway as well as in road environments show that satellite signals received by multipath are often used by GNSS receivers in the localization process. Thus, propagation characteristics of the satellite signals in an urban canyon configuration were characterized to determine when a signal received by reflected ray is used by the receiver or not. A criterion related to the satellite elevation is defined to improve the overall performance of the predictive tool. Comparisons with real measurements are commented on. Both simulations and measurements are very similar. [ABSTRACT FROM AUTHOR]

Global Navigation Satellite Systems (GNSS) such as GPS, already used in aeronautics for safety-related applications, can play a major role in railway safety by allowing a train to locate itself safely. However, in order to implement this positioning solution in any embedded system, its performances must be evaluated according to railway standards. The evaluation of GNSS performances is not based on the same attributes class than RAMS evaluation. Face to these diffculties, we propose to express the integrity attribute, performance of satellite-based localisation. This attribute comes from aeronautical standards and for a hybridised GNSS with inertial system. To achieve this objective, the integrity attribute must be extended to this kind of system and algorithms initially devoted to GNSS integrity monitoring only must be adapted. Thereafter, the formalisation of this integrity attribute permits us to analyse the safety quantitatively through the probabilities of integrity risk and wrong-side failure. In this paper, after an introductory discussion about the use of localisation systems in railway safety context together with integrity issues, a particular integrity monitoring is proposed and described. The detection events of this algorithm permit us to conclude about safety level of satellite-based localisation system. [ABSTRACT FROM AUTHOR]

The article presents information on several meeting on telecommunication and additive manufacturing which sponsored by Institute of Electrical and Electronics Engineers (IEEE) Communications Society that was held in 2017. Topics include security for 5G wireless communication system, autonomous vehicles, and optical networks.

Evaluating dependability of complex systems requires the evolution of the system states over time to be analysed. The problem is to develop modelling approaches that take adequately the evolution of the different operating and failed states of the system components into account. The Fault Tree (FT) is a well-known method that efficiently analyse the failure causes of a system and serves for reliability and availability evaluations. As FT is not adapted to dynamic systems with repairable multi-state components, extensions of FT (eFT) have been developed. However efficient quantitative evaluation processes of eFT are missing. Petri nets have the advantage of allowing such evaluation but their construction is difficult to manage and their simulation performances are unsatisfactory. Therefore, we propose in this paper a new powerful process to analyse quantitatively eFT. This is based on the use of PN method, which relies on the failed states highlighted by the eFT, combined with a new analytical modelling approach for critical events that depend on time duration. The performances of the new process are demonstrated through a theoretical example of eFT and the practical use of the method is shown on a satellite-based railway system. [ABSTRACT FROM AUTHOR]

According to the evolution tendency of the control decision process from a trackside to a train-borne system, various autonomous localization units for railway vehicles were developed. As recommended in railway standards, the design process of each system, here the autonomous localization units (LU), follows the V-model whose first step is to define its availability requirement in order to satisfy the global ETCS system requirements. The classical approach for assigning the subsystem availability is based on the assumption that failure parameters of other units are precisely known. This assumption is too restricted in reality due to the lack of information. In this paper, we propose a new approach that allows taking into account uncertainties in the dependability parameters of the ETCS components for identifying the upper threshold of the LU unavailability to reach ETCS availability requirements. Using fuzzy fault trees, the fuzzy unavailability of the ETCS without the autonomous LU is evaluated. Then, based on its membership function, we assess the satisfaction rate that an advanced ETCS with the autonomous LU can satisfy the ETCS availability target. [ABSTRACT FROM AUTHOR]

In global positioning systems (GPS), classical localization algorithms assume, when the signal is received from the satellite in line-of-sight (LOS) environment, that the pseudorange error distribution is Gaussian. Such assumption is in some way very restrictive since a random error in the pseudorange measure with an unknown distribution form is always induced in constrained environments especially in urban canyons due to multipath/masking effects. In order to ensure high accuracy positioning, a good estimation of the observation error in these cases is required. To address this, an attractive flexible Bayesian nonparametric noise model based on Dirichlet process mixtures (DPM) is introduced. Since the considered positioning problem involves elements of non-Gaussianity and nonlinearity and besides, it should be processed on-line, the suitability of the proposed modeling scheme in a joint state/parameter estimation problem is handled by an efficient Rao-Blackwellized particle filter (RBPF). Our approach is illustrated on a data analysis task dealing with joint estimation of vehicles positions and pseudorange errors in a global navigation satellite system (GNSS)-based localization context where the GPS information may be inaccurate because of hard reception conditions. [ABSTRACT FROM PUBLISHER]

As the modern navigation business evolves, demands for high-precision positioning in GNSS-challenged environments increase, and the integrated system composed of Global Navigation Satellite System (GNSS)-based Real-Time Kinematic (RTK), inertial system (INS), Light Detection and Ranging (LiDAR), etc., is accepted as the most feasible solution to the issue. For prior-map-free situations, as the only sensor with a global frame, RTK determines and maintains the global positioning precision of the integrated system. However, RTK performance degrades greatly in GNSS-challenged environments, and most of the existing integrated systems adopt loose coupling mode, which does nothing to improve RTK and, thus, prevents integrated systems from further improvement. Aiming at improving RTK performance in the RTK/LiDAR/INS integrated system, we proposed an innovative integrated algorithm that utilizes RTK to register LiDAR features while integrating the pre-registered LiDAR features to RTK and adopts parallel filters in the ambiguity-position-joint domain to weaken the effects of low satellite availability, cycle slips, and multipath. By doing so, we can improve the RTK fix rate and stability in GNSS-challenged environments. The results of the theoretical analyses, simulation experiments, and a road test proved that the proposed method improved RTK performance in GNSS-challenged environments and, thus, guaranteed the global positioning precision of the whole system. [ABSTRACT FROM AUTHOR]