Object Tracking using Unscented Kalman Filter

In object tracking applications, the inherent nonlinearities in both motion and observation equations can lead to significant errors when using conventional Kalman filters. The Unscented Kalman Filter (UKF) effectively addresses this limitation by employing a deterministic sampling approach that propagates sigma points through the nonlinear system dynamics, providing more accurate state estimation.