Target classification via labeling of subtarget motion patterns
Firooz A. Sadjadi · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2001
Tracking ground moving targets in cluttered environment is a challenging problem in airborne surveillance. In this paper, we present a novel approach for classifying targets by exploiting the formation patterns of their subtarget motion estimates. The target's moving parts formation patterns are represented in terms of dynamic random graphs and the classification problem is reduced to that of graph identification. Target and subtarget motions are estimated by means of estimating their joint state vectors probability density functions that can be solved via a number of methods.