A Kalman filter is a mathematical algorithm used for estimating the state of a dynamic system from a series of noisy measurements. It is widely used in various fields such as engineering, economics, and computer science to refine estimates of the true state of a system by incorporating information from both past estimates and current measurements. The Kalman filter is particularly useful in situations where the underlying system is not fully observable or where measurements are subject to noise or inaccuracies. It is based on a recursive algorithm that continuously updates the estimates of the system state as new measurements become available.