A Typical Example of Kalman Filter Implementation
A classic application of Kalman filtering involves predicting an object's position coordinates and velocity from a limited sequence of noisy observations. This algorithm finds extensive applications in various engineering fields including radar systems and computer vision, while also serving as a crucial topic in control theory and control systems engineering. In radar applications, for instance, the primary objective is target tracking where measurements of position, velocity, and acceleration are inherently noisy. Kalman filtering utilizes the target's dynamic information to eliminate noise effects, producing optimal estimates that can represent current position (filtering), future position (prediction), or past position reconstruction.