In this paper, a way of improving the positioning performance of the GNSS system through hybridization with distances derived from GSM power measurements was proposed. The GNSS/GSM Fusion algorithm was an APF (Auxiliary Particle Filter) algorithm with UKF (Unscented Kalman Filter) proposal and Rao-Blackwellisation allowing tight hybridization of GPS and GSM measurements. Scenario 1 and 2 showed an improvement in terms of accuracy and availability thanks to the use of GSM received powers in addition to GPS pseudoranges in a realistic scenario. Several perspectives can be given: First, the automatic estimation of hyperparameters: PF algorithms can be used to perform joint estimation of some global parameters (as for instance observation and evolution noises variances). This would give the fusion algorithm a better adaptability to local situations. Finally, the use of “multiple models” formulation can be envisaged: ability of PF algorithms to select automatically the most adapted model among a bank of available evolution and observation models. This would allow the algorithm to deal better with multipath effects.

The aim of this paper was to propose a way of improving the positioning performance of the GPS system through hybridization with distance measurements derived from GSM power measurements. Both GPS and GSM measurements were generated using simulation models. The algorithm chosen to perform the hybridization is a particle filter. Simulations showed that while accuracy can only be slightly improved, a position solution can be obtained even when the GPS system is not available, thus considerably improving availability.

The European satellite navigation system GALILEO will provide radionavigation signals for a variety of applications. Safety Of Life users will get a safe navigation service through ranging signals carrying integrity information. The Galileo Integrity Baseline algorithm includes the transmission of three parameters allowing users to monitor their integrity level. These parameters are the Signal-In-Space Accuracy (SISA: prediction of the minimum standard deviation of a Gaussian distribution overbounding the Signal-In-Space error in the fault-free case), the Signal-In-Space Monitoring Accuracy (SISMA: minimum standard deviation of a Gaussian distribution overbounding the difference between Signal- In-Space error and its estimation by ground control stations) and the Integrity Flag, which accounts for satellite status (it can be set to 'OK', 'DON'T USE' or 'NOT MONITORED'). These parameters are part of the input of the user integrity algorithm, which computes user integrity risk at the alert limit and compares it to the Integrity Risk requirement corresponding to user's phase of flight. The work presented in this paper studies the influence of the algorithm used for computation of SISMA on user integrity and system availability. The algorithms used to compute SISMA are the reference Least-Squares and several robust methods, designed to reject wrong measurements and decrease ground system False Alarm rate (fault-free satellites flagged 'DON'T USE').

The European satellite navigation system GALILEO will provide radio-navigation signals for a variety of applications. Safety Of Life users will get a safe navigation service through ranging signals carrying integrity information. The Galileo Integrity Baseline algorithm includes the transmission of three parameters allowing users to monitor their integrity level. These parameters are the Signal-In- Space Accuracy (SISA: prediction of the minimum standard deviation of a Gaussian distribution overbounding the Signal-In-Space error in the fault-free case), the Signal-In-Space Monitoring Accuracy (SISMA: minimum standard deviation of a Gaussian distribution overbounding the difference between Signal-In-Space error and its estimation by ground control stations) and the Integrity Flag, which accounts for satellite status (it can be set to “OK”, “DON’T USE” or “NOT MONITORED”). The work presented in this paper studies the possibility of computing SISMA using a statistically robust algorithm, so as to reject wrong measurements and decrease ground system False Alarm rate (fault-free satellites flagged “DON’T USE”).

This paper presents new concepts to address the air traffic complexity modeling problem. Two new geometrical metrics have been introduced and have been found very useful to capture typical features of traffic complexity. The covariance metric is very adapted to identify disorder in a set of speed vectors and can be applied for en route airspace (en route airspace is the airspace between airports). Similarly, the Koenig metric identifies easily the curl movement organizations and can be applied to areas around airports where air traffic control procedures impose turns on aircraft trajectories.

Nous commençons par une courte introduction des principes du positionnement GNSS précis par mesures de phase dites RTK (Real-Time Kinematic) et PPP (Precise Point Positioning). Ensuite nous présentons les résultats actuels du projet COPNAV en cours de l'action PTP de TESA. Le signal des satellites GNSS est poursuivi par des boucles à verrouillage de code, fréquence et phase. Les sorties utilisées pour le positionnement conventionnel sont celles fournies par la boucle de code. Pour le positionnement précis, on utilise les mesures de phase, moins bruitées et en particulier moins sensibles aux multitrajets. Ces mesures sont cependant difficiles d’exploitation à cause du nombre entier de cycle qu'il faut estimer (résolution d’ambiguïté), la phase étant mesurée à 2 près. Les méthodes de positionnement précis GNSS telles que RTK ou PPP se distinguent par les moyens et informations supplémentaires nécessaires à l’estimation des ambiguïtés et à la correction des mesures pour arriver à une précision centimétrique. Mais ces performances sont habituellement obtenues avec des récepteurs de haute qualité, dans des environnements dégagés. En environnements contraints (urbain, intérieur, etc.), la disponibilité du positionnement précis baisse considérablement du fait des fréquentes pertes de signal provoquant des sauts de cycle. Nous présenterons les principes de la technologie RTK et les résultats que nous avons obtenus en utilisant le logiciel RTKLIB avec un récepteur bas coût U-Blox NEO 7, dans des environnements contraints (urbain et urbain dense), associée à une méthode innovante de compensation des sauts de cycle.