Evaluating Extended Kalman Filter and Unscented Kalman Filter for accurate trajectory estimation

This paper evaluates two common methods for trajectory estimation: the Extended Kalman Filter (EKF), the Unscented Kalman Filter (UKF). The EKF and UKF are well-established recursive filtering techniques commonly used for nonlinear state estimation.The performance of these methods is compared through their implementation on a standard trajectory estimation problem, with a focus on assessing their accuracy.