Unscented Kalman Filter

The Unscented Kalman Filter (UKF) is a nonlinear estimation technique used to estimate the state of a system from noisy measurements, primarily by approximating probability distributions using a deterministic sampling method called the unscented transform. Current research focuses on applying UKFs in diverse fields, including autonomous driving (path tracking, multi-object tracking, velocity estimation), robotics (state estimation, control, sensor fusion), and aerospace (navigation, orbital debris tracking). The UKF's robustness and accuracy in handling nonlinear systems and non-Gaussian noise make it a valuable tool across numerous applications, improving performance in areas such as state estimation, control, and sensor fusion.