Lokalisierung eines Fahrzeugs mit einem Unscented Kalman Filter

Vehicle localization for autonomous driving is achieved by fusing GNSS, IMU, and LiDAR data with an Unscented Kalman Filter (UKF). The UKF’s performance is evaluated in the CARLA driving simulator and compared to an Error State Extended Kalman Filter (ESEKF), with higher accuracy in position and orientation estimation observed under sensor noise and signal loss. It is demonstrated that the UKF provides a more reliable solution for non‑linear vehicle state estimation.