Precise positioning of autonomous vehicles combining UWB ranging estimations with on-board sensors

• 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. © 2020 by the authors.

Nyckelord

Autonomous vehicle

Dynamic tests

Extended Kalman filter

High velocity

Precise positioning

RC car

Real outdoor environment

UWB

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