|Abstract:||Automobiles has become a very important means of transportation in modern society. Also, the car navigation services have changed people’s lives conveniently. However, the current navigation services does not meet the needs of all users. The car navigation works well on the open sky roads, but its performance becomes degraded in the urban canyon where multipath is severe. In addition, the navigation system does not operate properly in a tunnel or an indoor parking lot where the GNSS signal is cut off. Especially, in the case of indoor parking lot, there is a lot of demand for navigation service, but the navigation system does not operate from the moment the GPS signal is blocked. In hospitals, shopping malls, airports, etc., indoor or underground parking lots are so wide that it is difficult for the driver to know current location. Even if parking is done, it is not easy to memorize the parked position, and it is also difficult to search for the parked position. What if the navigation system guides you to an empty parking space closest to the destination? It will also be very convenient if the navigation system guides you to the parked location when you are finished with all your work. In this research, we present LTE signal based vehicle localization in the indoor parking lot. The purpose of this work is to estimate and track the location of vehicle in the indoor parking lot using only mobile phone. Since the proposed system utilizes LTE signals and internal sensor from mobile phone, no additional infrastructure installation is required. In this study, we use the received signal strength (RSS) of LTE to estimate the position of vehicle. Very few (one or two) LTE signals are received in the underground parking lot. In this situation, it is very difficult to estimate the position using the previous fingerprint method. The difference between the proposed system and the conventional fingerprinting method is that, instead of using only the currently RSS of LTE, an accumulated RSS while moving is utilized for the position estimation. It is possible to identify the RSS change in a specific space through the accumulated RSS pattern. The RSS pattern is compared with a previously stored radio map (database) to find the current location. As the length of the pattern increases, the number of candidates in the database that have similar correlation values to the pattern decreases. In addition, the estimated trajectory generated by moving the vehicle is also used to compare with the RSS pattern and radio map to enable more precise location estimation. To implement the proposed system, at first, we construct the LTE database in the test bed. The LTE RSS scanned at each reference point (RP) is stored in the LTE database. In positioning phase, the user receives the LTE RSS and stores it in the LTE buffer at regular intervals. Since LTE RSS is stored in the LTE buffer at regular intervals, it is necessary to convert the received LTE RSS in the time domain into a space region in order to compare the LTE buffer with the database. Therefore, it is essential to calculate the moved distance of the vehicle to improve the performance of the proposed system. The moved distance is calculated by the integrating the acceleration sensor of the mobile phone. However, the performance of acceleration sensors in the mobile phone is quite low that it is difficult to accurately estimate the moved distance of vehicle. To enhance the accuracy, the state of vehicle such as stopping, moving, and turning is recognized and applies it to the distance estimation. Also, if there are several speed bumps in the underground parking lot, it could be used to estimate the distance and position by detecting that the car has passed the speed bump. To verify the performance of the proposed system, experiments were conducted at the E-mart underground parking lot in Jayang-dong, Seoul. The underground parking lot of the shopping mall is capable of parking about 500 vehicles on one floor. In the experiment, we identify that one LTE physical cell identity (PCI) is received and two LTE antennas are installed to extend the LTE signal coverage. The proposed system is expected to be able to estimate the position error of less than 15 meters in the parking lot. Conclusion In this research, we present the localization system based on the LTE RSS for the vehicle location estimation in the indoor or underground parking lot. The proposed system estimates the position using the accumulated pattern of LTE RSS while moving. In addition, the performance of the system is improved by using the state information of the vehicle estimated using the acceleration sensor. We expect that driver would be use the enhanced car navigation service through this technology in the indoor or underground parking lot.|
Proceedings of the 32nd International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2019)
September 16 - 20, 2019
Hyatt Regency Miami
|Pages:||378 - 415|
|Cite this article:||
Shin, Beomju, Lee, Jung Ho, Lee, Taikjin, Kee, Changdon, "LTE Signal Based Vehicle Localization in Indoor Parking Lot using Mobile Phone," Proceedings of the 32nd International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2019), Miami, Florida, September 2019, pp. 378-415.
ION Members/Non-Members: 1 Download Credit