Multiple model estimator for a tightly coupled HRR automatic target recognition and MTI tracking system

The goal of this research is to exploit couplings between tracking and ATR systems employing high range resolution radar (HRRR) and moving target indicator (MTI) measurements. As will be shown, these systems are coupled via pose, kinematic, and association constraints. Exploiting these couplings results in a tightly coupled system with significantly improved performance. This problem deals with two different types of spaces, namely the continuous space kinematics (e.g. position and velocity) and the discrete space target type. A multiple model estimator (MME) was chosen for this problem. The MME consist of a bank of extended Kalman filters (one for each target type). The continuous space kinematics are dealt with via these extended Kalman filter. Further, the probability of each Kalman filter is computed and used to determine the corresponding discrete space target probability. Presented in this paper are empirical results that show improvement over conventional techniques.