Integrity monitoring for mobile users in urban environment (2016)

Satellite navigation is a promising technology for terrestrial applications that requires the monitoring of the vehicle position thanks to costly ground infrastructures. In the rail domain, the European train control system (ETCS) relies on a combination of radio beacons (that provides information of absolute position) and odometry to propagate the position between two balises groups. The use of Global Navigation Satellite Systems (GNSS) in ETCS has been proposed in order to reduce the amount of beacons. In the road domain, the GNSS is one of the technologies recommended by the European Union directive for Electronic Toll Collection (ETC), and GNSS based ETC systems already exists for heavy good transportation in Germany (Toll Collect) and Slovakia (MYTO). For these two applications that are either safety critical (train control) or liability critical (toll collection), it is not acceptable to estimate the position of the vehicle with a large error without warning the system within a sufficiently short delay. It is firstly necessary to define the operational requirements for the navigation system for these terrestrial applications. This kind of problematic has already been handled in the context of civil aviation which is also a critical application, but currently, the operational requirements associated to GNSS are not standardized for the train control and ETC. Based on the model of civil aviation, a state of the art of possible requirements for train control and electronic toll collection is proposed. For train control, a solution based on redundant independent GNSS constellations has been proposed in order to relax the integrity risk requirements on each sub constellation. In the case of ETC, the requirements will depend on the case of study and are indirectly imposed by the toll charger. For terrestrial applications, the vehicles are likely to operate in constrained environment (including urban environment). In urban environment, the performances of GNSS are highly degraded due to multipath interference, tracking of non-line-of-sights and masking effects. These phenomena are likely to degrades the accuracy, integrity, availability and continuity of the GNSS based positioning system. It is proposed to augment the solution proposed for each application by integrating measurements from a six axis inertial measurement unit which are insensitive to the receiver surrounding environment. Integrating information from other sensors such as a track database for train control or odometry for toll collection is investigated. The nominal error models and fault modes of the sensors are then studied. The nominal error models will be used to weight the measurements in the fusion algorithm and to test the performances of the fusion algorithm by realistic simulations. In particular, the characterization of the distribution and the modelling of the errors dues to multipath and non-line-of-sights in urban environment is studied on simulator and on a data collection campaign conducted in Toulouse downtown (France) and its surroundings. The extended Kalman filter used to fuse the GNSS measurements and the measurements from other sensors are then presented. A tight coupling architecture in closed loop is presented as it is the most adapted to the cases of study. The integration of a track database in the solution is discussed in the case of train control. The extension of the solution to the multi-constellation case is also presented. The solutions have been validated and tested on a simulator as well as in real condition in Toulouse downtown. It is shown that additional sensors such as track database or wheel speed sensors enable to limit the drift of the position error in costing/degraded constellation condition. Then, it is proposed to improve the robustness and the reliability of the GNSS measurements in urban area by developing multipath detection algorithms at the signal processing level. A detection algorithm based on the real time analysis of the correlation function is proposed. This algorithm aims at assisting the integrity monitoring algorithm upstream by protecting it against the faults due to multipath with large amplitudes. However, this algorithm does not protect against non-line-of-sights that can lead to integrity failures as this phenomenon is not associated with any abnormal distortion. Several methods based on the elevations of the satellites, the signal to noise ratio, or the coherence of the measurements based on the comparison with non GNSS sensors measurements have been studied in order to protect the solution against this phenomenon. Two snapshots integrity monitoring algorithms adapted to the Kalman filter are presented. Finally, the performances of these algorithms are tested on the data collected in Toulouse downtown and surroundings. The improvement obtained by assisting the integrity monitoring algorithm upstream by testing the quality of the measurement is quantized (with respect to a simple inflation of the nominal models in urban environments).