İntroduction to Kalman filter

In 1960, Rudolph Emil Kalman who is Electrical Engineer published the Kalman Filter. Kalman Filter is a powerful recursive state space model based algorithm which make estimation past, present and future while the system has a noise measurements. And application area is economics, biology, medicine, robotics, navigation, tracking objects, stabilizing, radar, laser scanner, space, engineering and other sector which systems are making prediction.

Kalman filter work on noise measurements with recursive least square method and make best prediction. After prediction filters compare real values and predicted values and according this ratio filter generate Kalman Gain and uses this information on the new estimation, this is the best way of prediction with disturbances.

The Kalman filter is named after Rudolph E.Kalman, who in 1960 published his famous paper describing a recursive solution to the discrete-data linear filtering problem (Kalman 1960) [11]. It is the optimal estimator for a large class of problems, finding the most probable state as an unbiased linear minimum variance estimate of a system based on discrete observations of the system and a model which describes the evolution of the system [5].


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