Tracking of subsequently fired projectiles

Polat, Mehmet
In conventional tracking algorithms the targets are usually considered as point source objects. However, in realistic scenarios the point source assumption is often not suitable and estimating the states of an object extension characterized by a collectively moving ballistic object group (cluster) becomes a very critical and relevant problem which has applications in the defense area. Recently, a Bayesian approach to extended object tracking using random matrices has been proposed. Within this approach, ellipsoidal object extensions are modeled by random matrices and treated as additional state variables to be estimated. In this work we propose to use a slightly modified version of this new approach that simultaneously estimates the ellipsoidal shape and the kinematics of a group of ballistic targets. Target group that is tracked consists of subsequent projectiles. We use JPDAF framework together with the new approach to emphasize the pros and cons of both approaches. The methods are demonstrated and evaluated in detail by making various simulations.