Kalman filters are used to optimally estimate the variables of interests when they can't be measured directly, but an indirect measurement is available. They are also used to find the best estimate of states by combining measurements from various sensors in the presence of noise.

What is better than a Kalman Filter?

The unscented Kalman filter (UKF) is a useful alternative to the extended Kalman filter (EKF) for tracking with nonlinear dynamics models and when the measurements are nonlinear functions of the target state. ... This paper reviews previous work showing that the UKF is one among many numeric integration-based filters.

How does Kalman Filter work?

The filter estimates the current measurement by multiplying the predicted state by the measurement matrix. The residual, ∼yk , is later then multiplied by the Kalman gain, Kk , to provide the correction, Kk∼yk , to the predicted estimate ˆx−k .