Information Fusion in a Hybrid Tightly Coupled GPS/Dead-Reckoning Positioning System

The subject of this article is about study and realisation of a tight hybrid filter for vehicle positioning in dense urban area. In our approach we fused the measurements coming from the sensors in a hybrid filter at the pseudo-ranges level. The proposed filter combines the "observables" (measurements) of phase and code of a GPS receiver with the measurements of an odometer and a gyrometer. We describe in this article the design of the fusion filter inspired of the distributed "track to track" Kalman filter architecture. In our approach the pseudo-ranges predictions, construct with the phase measurements of the GPS and the dead-reckoning measurements system, are fused. The fused predictions are them corrected with the GPS code measurements of the pseudo-ranges. We use the classical snapshot least squares estimation technique to calculate the position with the estimated pseudo-ranges. We present in this article different simulations results obtained in a real dense urban context. We show that the tight hybrid filter we propose gives a location at least as precise as the classical loosely coupled hybrid filter. This result is obtained for a number of satellites lower than four and various values of the HDOP (horizontal dilution off precision)