Positioning Estimation of Autonomous Car using Extended Kalman Filter

Abstract

In this paper, the Extended Kalman Filter (EKF) is proposed to estimate the position of an autonomous car. The EKF is chosen since it is the widely used estimation algorithm for nonlinear systems. The design of EKF is relatively easy compared to other versions of the KF modification. The used mathematical model in this simulation is kinematics in terms of nonlinear system. Based on the simulation results, the EKF can estimate the position of an autonomous car with comparatively small errors between the actual and the estimate positions. In this case, the reported RMSE for x-position and y-position is 0.1733 m and 0.1437 m, respectively. According to those results, the EKF method is applicable for the positioning estimation of autonomous cars.