A Hybrid Positioning Strategy for Vehicles in a Tunnel Based on RFID and In-Vehicle Sensors

Sensors

卷:14

Bin Li¹  Weigong Zhang²  Xu Li²  Xiang Song²  Wencheng Tang³ 

[1] Key Laboratory of Technology on Intelligent Transportation Systems, Ministry of Transport,Beijing 100088, China;

[2] School of Instrument Science and Engineering, Southeast University, Nanjing 210096, China;

[3] School of Mechanical Engineering, Southeast University, Nanjing 210096, China;

关键词: vehicle positioning;    sensor fusion;    tunnel;    RFID;    interactive multiple model;   

DOI  :  10.3390/s141223095

来源: DOAJ

【 摘 要 】

Many intelligent transportation system applications require accurate, reliable, and continuous vehicle positioning. How to achieve such positioning performance inextended GPS-denied environments such as tunnels is the main challenge for land vehicles. This paper proposes a hybrid multi-sensor fusion strategy for vehicle positioning in tunnels. First, the preliminary positioning algorithm is developed. The Radio Frequency Identification (RFID) technology is introduced to achieve preliminary positioning in the tunnel. The received signal strength (RSS) is used as an indicator to calculate the distances between the RFID tags and reader, and then a Least Mean Square (LMS) federated filter is designed to provide the preliminary position information for subsequent global fusion. Further, to improve the positioning performance in the tunnel, an interactive multiple model (IMM)-based global fusion algorithm is developed to fuse the data from preliminary positioning results and low-cost in-vehicle sensors, such as electronic compasses and wheel speed sensors. In the actual implementation of IMM, the strong tracking extended Kalman filter (STEKF) algorithm is designed to replace the conventional extended Kalman filter (EKF) to achieve model individual filtering. Finally, the proposed strategy is evaluated through experiments. The results validate the feasibility and effectiveness of theproposed strategy.

【 授权许可】

Unknown