Volume 21 Issue 2
Aug.  2021
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Article Navigation >  Journal of Traffic and Transportation Engineering  > 2021  >  21(2): 256-266
ZHU Bing, TAO Xiao-wen, ZHAO Jian, KE Min, WANG Zhi-wei, LI Xin. Two-stage UWB positioning algorithm of intelligent vehicle[J]. Journal of Traffic and Transportation Engineering, 2021, 21(2): 256-266. doi: 10.19818/j.cnki.1671-1637.2021.02.022
Citation: ZHU Bing, TAO Xiao-wen, ZHAO Jian, KE Min, WANG Zhi-wei, LI Xin. Two-stage UWB positioning algorithm of intelligent vehicle[J]. Journal of Traffic and Transportation Engineering, 2021, 21(2): 256-266. doi: 10.19818/j.cnki.1671-1637.2021.02.022
shu

Two-stage UWB positioning algorithm of intelligent vehicle

doi: 10.19818/j.cnki.1671-1637.2021.02.022
  • 1.

    State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130022, Jilin, China

  • 2.

    College of Aeronautical Combat Services, Aviation University of Air Force, Changchun 130021, Jilin, China

Funds:

National Key Research and Development Program of China 2018YFB0105103

National Natural Science Foundation of China 51775235

Jilin Provincial Development and Reform Commission Science and Technology Project 2019C036-6

Graduate Innovation Fund of Jilin University 101832020CX130

Graduate Innovation Fund of Jilin University 101832020CX127

More Information
  • Author Bio:

    ZHU Bing(1982-), male, professor, PhD, zhubing@jlu.edu.cn

  • Corresponding author: ZHAO Jian(1978-), male, professor, PhD, zhaojian@jlu.edu.cn
  • Received Date: 2020-12-03
  • Publish Date: 2021-04-01
    Abstract
  • To improve the driving reliability of intelligent vehicles, taking the ultra-wide band (UWB) as the research object, the two-stage UWB positioning algorithm for intelligent vehicles was studied. The basic principles and error sources of intelligent vehicle's UWB positioning algorithm were analyzed. A two-stage UWB positioning algorithm was established to filter the ranging values and calculate the weighted positions. In the filtering stage of ranging values, small probabilities and large interference events were eliminated through the Gaussian filtering. In the calculation stage of weighted positions, the final position coordinates were obtained by weighting the position coordinates of multiple ranging points to effectively reduce the errors caused by non-line-of-sight and multipath effects. The errors of multipath effects were effectively reduced by using the anti-multipath antennas, and the static and motion compensation strategies were established to effectively reduce the errors caused by hardware problems, such as the crystal deviation of the device. A simulation environment for UWB random ranging values under certain range variance constraints was built by using the MATLAB/Simulink simulation platform. The algorithm was simulated and compared with the trilateral positioning algorithm and the trilateral centroid positioning algorithm, and the impact of the number of base stations on positioning precision was analyzed. A physical UWB test system was built, the positioning precision of UWB equipment was evaluated, and the error compensation was performed. The two-stage UWB positioning algorithm was tested on a real vehicle. Simulation result shows that the mean values of positioning errors in the east and north directions can be as small as 0.382 3 and 0.447 0 m, respectively. The compensated UWB positioning trajectory is closer to the trajectory shown by RT3002. The average values of the east and north trajectory errors are 0.049 2 and 0.017 8 m, and the root mean square errors are 0.069 8 and 0.026 4 m, respectively. Thus, the proposed two-stage UWB positioning algorithm can meet the positioning requirements of intelligent vehicles, and has the advantages of high precision, low cost, and good stability. 2 tabs, 20 figs, 32 refs.

     

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