The object position estimation based on limited number of observations

The highly limited number of observation results in the increase of the prediction errors. In such case the linear Kalman filter (KF) will work within the unsteady state, which can lead to unpredictable results. The paper presents an alternative, simplified methods for the tracked object position prediction with the linearization of the trajectory. The obtained results are compared with the KF predictions and the true object's position.