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.