LTE RSSI Based Vehicular Localization System in Long Tunnel Environment - Shin, Beom ju; Jung Ho Lee; Kim, Chongwon; Jeon, Sanghoon; Lee, Taik jin (Institute of Electrical and Electronics Engineers, 2023)
Current navigation systems rely heavily on global navigation satellite systems (GNSSs), which provide stable positioning results in open-sky environments but exhibit severe performance degradation in areas where the signal is compromised, such as dense urban environments, underground parking lots, and tunnels. Current navigation systems use an initial entry velocity to estimate a vehicle's position in a tunnel. Therefore, when the speed of a vehicle changes, a corresponding error occurs with respect to the determined position of the vehicle. This study proposes a novel localization technology to estimate a vehicle's position using long-term evolution (LTE) signals measured using a smartphone in a tunnel. Many antennas are installed along the length of the tunnel to increase LTE coverage. Thus, the LTE received signal strength indicator (RSSI) forms a unique pattern with several peaks in the tunnel. The accumulated LTE RSSI pattern was used to estimate the vehicle position in the tunnel. After the LTE fingerprint inside the tunnel was constructed, the position with the highest correlation with the LTE RSSI sequence of the user buffer was determined as the current vehicle location. To demonstrate the feasibility of the proposed system, we conducted an extensive field test in an actual tunnel using various off-the-shelf smartphones. Experimental results show that the proposed technology provides stable performance throughout the tunnel space.