Applications of Kalman and Extended Kalman Filtering to Target Tracking

This study deals with the famous trackers named Kalman and extended Kalman filters. This is introduced by describing the state space representation approach to model the target system. A modification to the state prediction equation of Kalman and extended Kalman filters is given in order to offer an ability of multi-step ahead prediction of the target future position. The problem of missed measurements, with different percentages of missing, is studied and a method to estimate these missed measurements is then suggested. Some simulation experiments are performed and indicated that Kalman filtering techniques are promising when they deal with target tracking problem.