Performance evaluation of vehicle positioning system using multi-sensor in GNSS blockage area

Vehicle navigation systems, which rely on GNSS(Global Navigation SatelliteSystem) signal, have limitations that it is impossible to position the vehicle in GNSS signalshaded areas such as building forests and tunnels. Due to the development of MEMS(Microelectromechanical Systems) technology, a variety of low-cost MEMS-IMU(InertialMeasurement Unit)s have been launched, and studies combining GNSS and MEMS-IMU havebeen actively conducted. MEMS-based IMU has an advantage in terms of the cost, but its errorrapidly increases in a short time, compared with the conventional inertial sensor. To overcomethis problem, additional sensors are needed to obtain more observations(Brown, 2005).Recently, vehicles equipped with ADAS(Advanced Driver Assistance System) have beenreleased for the convenience and the safety of the driver(Heo, 2009). To run the ADAS,vehicles with various sensors, such as wheel speed sensors, yaw rate sensor and steering anglesensors, are on the market. Therefore, it is expected that the positioning performance will beimproved if additional observations are utilized by using various sensors as described above.In this study, GNSS, MEMS-IMU, on-board vehicle sensor based car positioning system isdeveloped. The vehicle positioning algorithm is implemented based on an extended Kalmanfilter and adopts a closed loop. As the result, compared with the GNSS and MEMS-IMUcombination, performance improves greatly depending on whether the wheel speed sensor isadded in the GNSS signal blockage. The most stable positioning performance was confirmedwhen all available sensors were used. In the 45seconds of 10 GNSS signal blockages, mean ofhorizontal error was 5.31m.