Precise Positioning of Autonomous Vehicles Combining UWB Ranging Estimations with On-Board Sensors

Javier San Martín,Leticia Zamora-Cadenas,Bo Joel Svensson,Ainhoa Cortés

doi:10.3390/electronics9081238

Javier San Martín, Leticia Zamora-Cadenas + Show 2 more

Open Access

https://doi.org/10.3390/electronics9081238

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Abstract

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.

Highlights

The vehicle industry is focusing on developing autonomous vehicles in order to improve driving safety and efficiency
This paper is focused on the study of a positioning system based on the UWB/Inertial Measurement Unit (IMU)/Odometry fusion as a complementary system to those based on Global NavigationSatellite Systems (GNSS) signals
Unlike inertial and odometry data, the UWB ranging estimates have a bounded error over time, indicating that their error does not increase with time

Summary

Introduction

The vehicle industry is focusing on developing autonomous vehicles in order to improve driving safety and efficiency. An autonomous vehicle requires to know with a high accuracy its global position This issue has been covered by Global Navigation. Among other requirements, an unobstructed Line-of-Sight (LOS) to four or more satellites in order to provide an enough accurate positioning solution. In some environments, such as urban canyons or tunnels, this can be a great challenge, since the satellite signals need to overcome numerous obstacles before reaching the vehicle’s receiver. When GNSS signals are not available, the positioning is only based on the vehicle’s inertial and odometry data [2]. If GNSS signals are blocked during a long period of time, the vehicle’s position will be extremely inaccurate

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