In this paper, we analyze the performance of a positioning system based on the fusion of
Ultra-Wideband (UWB) ranging estimates together with odometry and inertial data from the vehicle.
For carrying out this data fusion, an Extended Kalman Filter (EKF) has been used. Furthermore,
a post-processing algorithm has been designed to remove the Non Line-Of-Sight (NLOS) UWB
ranging estimates to further improve the accuracy of the proposed solution. This solution has been
tested using both a simulated environment and a real environment. This research work is in the scope
of the PRoPART European Project. The different real tests have been performed on the AstaZero
proving ground using a Radio Control car (RC car) developed by RISE (Research Institutes of Sweden)
as testing platform. Thus, a real time positioning solution has been achieved complying with the
accuracy requirements for the PRoPART use case