Algorithm for missile detection from radar data

Algorithm for identification of the characteristics of a missile and of its trajectory on the basis of radar measurements has been proposed. The effectiveness of the proposed algorithm involves the combined use of maximum likelihood estimate (MLE) and parameters estimate as well as the use of an extended Kalman filter (EKF), a real-time method. Calculations involved missile detection from deterministic data and from measures corrupted by noise including four missile fundamental parameters and six state variables. The analytic estimate thus obtained, provided clue for the convergence of a post-processing algorithm based on the MLE method. The EKF was successfully used in the determination of the state vector that determines the trajectory in the ballistic phase. Such a combined use of batch-detection algorithms for the boosted phase and real-time detection algorithms for the ballistic and reentry phases proves to be an effective solution.