Target tracking using adaptive Kalman Filter

In this paper Ballistic missile is tracked in re-entry phase using Extended Kalman Filter(EKF) which is mainly used in nonlinear estimation. Target tracking of Ballistic Missile has been done using EKF and further the result of EKF is compared with Adaptive extended Kalman filter (AEKF). The basic difference between them is that EKF use a priori guess to estimate the process and measurement noise while AEKF updates them in every measurement step but with the regular change in the circumstances priori guess can be estimated with larger error hence AEKF can stand better in that case. The simulation results show that AEKF is better in performance as compared to EKF in terms of accuracy as well as covariance.