Extended Kalman Filter
The Extended Kalman Filter (EKF) is a nonlinear version of the Kalman Filter used for state estimation in systems with nonlinear dynamics or measurement models. It linearizes the nonlinear functions around the current state estimate using a first-order Taylor series expansion, then applies the standard Kalman Filter equations to the linearized system. This makes it widely applicable in robotics, navigation, and control systems where models are not strictly linear.
Developers should learn EKF when working on state estimation problems in nonlinear systems, such as in robotics for sensor fusion (e.g., combining IMU and GPS data), autonomous vehicles for localization, or aerospace applications for tracking. It is particularly useful when linear approximations are sufficient and computational efficiency is needed compared to more complex nonlinear filters like the Unscented Kalman Filter.