ABSTRACT

Many defense situations require weapon delivery systems that should have an accurate prediction of launch and impact points of targets detected during a part of their trajectory. It is important to know from where the target had been launched and whether the target is from an enemy territory or friendly territory. Kalman filter-based filters have been used to predict such trajectories. If the entire flight trajectory is observed then the estimation of the launch and impact points can be made straightforward using the Kalman filter. Kalman filter provides minimum mean square error when the measurements are in Cartesian coordinates, measurements are independent and Gaussian distribution and target behaviour is known. The dynamic model of the stochastic system must be constructed in the form of state-space representation in order to utilize it into the Kalman filter. The Kalman filter and RTS smoother techniques are implemented and demonstrated using PC MATLAB.