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Vehicle localization using doppler shift and time of arrival measurements in a tunnel environment

Rreze Halili, Noori BniLam, Marwan Yusuf (UGent) , Emmeric Tanghe (UGent) , Wout Joseph (UGent) , Maarten Weyn and Rafael Berkvens
(2022) SENSORS. 22(3).
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Abstract
Most applications and services of Cooperative Intelligent Transport Systems (C-ITS) rely on accurate and continuous vehicle location information. The traditional localization method based on the Global Navigation Satellite System (GNSS) is the most commonly used. However, it does not provide reliable, continuous, and accurate positioning in all scenarios, such as tunnels. Therefore, in this work, we present an algorithm that exploits the existing Vehicle-to-Infrastructure (V2I) communication channel that operates within the LTE-V frequency band to acquire in-tunnel vehicle location information. We propose a novel solution for vehicle localization based on Doppler shift and Time of Arrival measurements. Measurements performed in the Beveren tunnel in Antwerp, Belgium, are used to obtain results. A comparison between estimated positions using Extended Kalman Filter (EKF) on Doppler shift measurements and individual Kalman Filter (KF) on Doppler shift and Time of Arrival measurements is carried out to analyze the filtering methods performance. Findings show that the EKF performs better than KF, reducing the average estimation error by 10 m, while the algorithm accuracy depends on the relevant RF channel propagation conditions and other in-tunnel-related environment knowledge included in the estimation. The proposed solution can be used for monitoring the position and speed of vehicles driving in tunnel environments.
Keywords
RF, localization, GNSS, tunnel, C-ITS, KALMAN FILTER, PROPAGATION, COMMUNICATION, TRACKING, IMPACT, ANGLE

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MLA
Halili, Rreze, et al. “Vehicle Localization Using Doppler Shift and Time of Arrival Measurements in a Tunnel Environment.” SENSORS, vol. 22, no. 3, 2022, doi:10.3390/s22030847.
APA
Halili, R., BniLam, N., Yusuf, M., Tanghe, E., Joseph, W., Weyn, M., & Berkvens, R. (2022). Vehicle localization using doppler shift and time of arrival measurements in a tunnel environment. SENSORS, 22(3). https://doi.org/10.3390/s22030847
Chicago author-date
Halili, Rreze, Noori BniLam, Marwan Yusuf, Emmeric Tanghe, Wout Joseph, Maarten Weyn, and Rafael Berkvens. 2022. “Vehicle Localization Using Doppler Shift and Time of Arrival Measurements in a Tunnel Environment.” SENSORS 22 (3). https://doi.org/10.3390/s22030847.
Chicago author-date (all authors)
Halili, Rreze, Noori BniLam, Marwan Yusuf, Emmeric Tanghe, Wout Joseph, Maarten Weyn, and Rafael Berkvens. 2022. “Vehicle Localization Using Doppler Shift and Time of Arrival Measurements in a Tunnel Environment.” SENSORS 22 (3). doi:10.3390/s22030847.
Vancouver
1.
Halili R, BniLam N, Yusuf M, Tanghe E, Joseph W, Weyn M, et al. Vehicle localization using doppler shift and time of arrival measurements in a tunnel environment. SENSORS. 2022;22(3).
IEEE
[1]
R. Halili et al., “Vehicle localization using doppler shift and time of arrival measurements in a tunnel environment,” SENSORS, vol. 22, no. 3, 2022.
@article{01GQJ5XQ610Z1VA6MPJT0MRHMG,
  abstract     = {{Most applications and services of Cooperative Intelligent Transport Systems (C-ITS) rely on accurate and continuous vehicle location information. The traditional localization method based on the Global Navigation Satellite System (GNSS) is the most commonly used. However, it does not provide reliable, continuous, and accurate positioning in all scenarios, such as tunnels. Therefore, in this work, we present an algorithm that exploits the existing Vehicle-to-Infrastructure (V2I) communication channel that operates within the LTE-V frequency band to acquire in-tunnel vehicle location information. We propose a novel solution for vehicle localization based on Doppler shift and Time of Arrival measurements. Measurements performed in the Beveren tunnel in Antwerp, Belgium, are used to obtain results. A comparison between estimated positions using Extended Kalman Filter (EKF) on Doppler shift measurements and individual Kalman Filter (KF) on Doppler shift and Time of Arrival measurements is carried out to analyze the filtering methods performance. Findings show that the EKF performs better than KF, reducing the average estimation error by 10 m, while the algorithm accuracy depends on the relevant RF channel propagation conditions and other in-tunnel-related environment knowledge included in the estimation. The proposed solution can be used for monitoring the position and speed of vehicles driving in tunnel environments.}},
  articleno    = {{847}},
  author       = {{Halili, Rreze and  BniLam, Noori and Yusuf, Marwan and Tanghe, Emmeric and Joseph, Wout and Weyn, Maarten and Berkvens, Rafael}},
  issn         = {{1424-8220}},
  journal      = {{SENSORS}},
  keywords     = {{RF,localization,GNSS,tunnel,C-ITS,KALMAN FILTER,PROPAGATION,COMMUNICATION,TRACKING,IMPACT,ANGLE}},
  language     = {{eng}},
  number       = {{3}},
  pages        = {{20}},
  title        = {{Vehicle localization using doppler shift and time of arrival measurements in a tunnel environment}},
  url          = {{http://doi.org/10.3390/s22030847}},
  volume       = {{22}},
  year         = {{2022}},
}
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