A Position Estimation of Vehicle using Adaptive Kalman Filter based on Moving Pattern
Youngwan Cho, Hyun‐Kyu Choi · Advanced Science and Technology Letters · 2014
Generally, in railroad and aviation fields which require high stability systems, detecting global position with credibility is an essential factor. In this thesis, a technique to detect global position of vehicles (train service) moving in a set pattern in a limited situation will be introduced. An adaptive position filter will be used for the technique to detect global location which was designed based on Rudolf Emil Kalman’s Kalman filter. Also, to position the position data estimated by the adaptive position filter in actual road and railroads, a map matching technique was used to match road and railroads to estimate the final global position.