Integrated Positioning Method for Intelligent Vehicle Based on GPS and UWB

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Authors Abstract
Content
Knowledge of intelligent vehicle absolute position is a vital premise for the implementation of decision programming, kinematic and dynamics control. In order to achieve high accuracy positioning and reduce running cost as much as possible under all operating conditions, this paper proposed an integrated positioning method based on GPS and Ultra Wide Band(UWB) for intelligent vehicle’s navigation and position system. In this method, GPS and UWB are alternately active according to the confidence level of GPS signal. When the vehicle is traveling in a wide-open area and GPS signal is well received, the positioning results of Dead Reckoning system are corrected by the low frequency positioning output from GPS. During the correcting process, in order to realize the better fusion of measurement data, a simplified federal Kalman filter was designed by using indirect method. When the vehicle is in places where GPS signal can hardly be received such as tunnel, the positioning results based on UWB positioning technology can be adopted to substitute the lost GPS signal for vehicle integrated positioning. The algorithm used in the UWB positioning technology was two-phase positioning algorithm based on the signal arrival time, and Gaussian filtering method was also used in the pretreatment process of distance measuring values. Finally, a working test under the typical condition was conducted on the Matlab/Simulink-Carsim co-simulation platform. Simulation results demonstrate that even the vehicle is in the scenario without GPS and sensors are low cost, a better positioning accuracy can be still achieved with the integrated positioning method proposed in this paper.
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DOI
https://doi.org/10.4271/07-11-01-0004
Pages
8
Citation
Ke, M., Zhu, B., Zhao, J., and Deng, W., "Integrated Positioning Method for Intelligent Vehicle Based on GPS and UWB," SAE Int. J. Passeng. Cars – Electron. Electr. Syst. 11(1):40-47, 2018, https://doi.org/10.4271/07-11-01-0004.
Additional Details
Publisher
Published
Sep 23, 2017
Product Code
07-11-01-0004
Content Type
Journal Article
Language
English