TY - CHAP
T1 - 5G mmWave Vehicular Tracking
AU - Kim, Hyowon
AU - Wymeersch, Henk
AU - Garcia, Nil
AU - Seco-Granados, Gonzalo
AU - Kim, Sunwoo
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/7/2
Y1 - 2018/7/2
N2 - Vehicle positioning based on GPS is limited due to multipath and blockage. 5G mmWave signals can provide an attractive complement, as it is possible to estimate the state of a vehicle (position and heading) from transmissions from a single base station. We propose a Bayesian 5G mmWave tracking filter, which explicitly relies on mapping the radio environment. The filter thus solves a novel type of simultaneous localization and mapping problem, which enables estimating not only the vehicle heading and position, but also its clock bias.
AB - Vehicle positioning based on GPS is limited due to multipath and blockage. 5G mmWave signals can provide an attractive complement, as it is possible to estimate the state of a vehicle (position and heading) from transmissions from a single base station. We propose a Bayesian 5G mmWave tracking filter, which explicitly relies on mapping the radio environment. The filter thus solves a novel type of simultaneous localization and mapping problem, which enables estimating not only the vehicle heading and position, but also its clock bias.
UR - http://www.scopus.com/inward/record.url?scp=85062986581&partnerID=8YFLogxK
U2 - 10.1109/ACSSC.2018.8645553
DO - 10.1109/ACSSC.2018.8645553
M3 - Chapter
AN - SCOPUS:85062986581
T3 - Conference Record - Asilomar Conference on Signals, Systems and Computers
SP - 541
EP - 547
BT - Conference Record of the 52nd Asilomar Conference on Signals, Systems and Computers, ACSSC 2018
A2 - Matthews, Michael B.
ER -