Enhanced Ballistic Trajectory Estimation from Radar Data Using the Cubature Kalman Filter

This paper investigates the use of the Cubature Kalman Filter (CKF) for estimating the trajectory of a projectile with known ballistic parameters using simulated radar measurements from a Weapon Locating Radar. The CKF is a nonlinear filtering technique with enhanced accuracy and numerical stability compared to the Extended Kalman Filter and the Unscented Kalman Filter. We evaluate the Cubature Kalman Filter performance under realistic measurement noise and dynamic conditions. The simulation results demonstrate improved tracking accuracy and robustness, highlighting its potential as a reliable solution for ballistic trajectory estimation in defense applications.