GNSS Positioning in Critical Scenarios: Hybrid Data Fusion with Communications Signals

In critical situations (e.g., urban canyons) for global navigation satellite systems (GNSSs) only less than the required four satellites can be accessed, and hence, just a limited positioning performance can be achieved. This paper covers the improvement of GNSS based positioning in these critical scenarios by hybrid data fusion (HDF) algorithms using additional measurements from a communications system. Moreover, this HDF is integrated in a tracking algorithm which exploits an extended Kalman filter (EKF) for further performance improvement. Simulation results show the ability of this approach to compensate the lack of satellites by additional timing measurements from a future 3GPP-LTE communications system. Contrary to state-of-the-art work, this paper analyzes the performance in a fairly realistic manner especially by taking into account raytracing simulations to obtain a coherent environment.