Ballistic Rockets Tracking: Kalman versus αβγ Filters

Abstract

This article presents the problem of tracking ballistic rockets through the propelled and ballistic stages using measured radar signal processing. We developed a dynamic model of a moving target. We have compared the performance of the estimation through quadratic mean error of the αβγ and Kalman filters. The results show that the Kalman filter has a better performance, it combines the statistical efficiency with a modest computational effort. This conclusion is valid when the target's ballistic coefficient is known a priori.