Optimum tracking and target identification using GMTI and HRR profiles
Ronald L. Levin, John H. Kay · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2000
The field of moving target Automated Target Recognition (ATR) relies on the exploitation of one-dimensional high range resolution (HRR) profiles. Individual profiles can contain a large amount of target information; however, the evidence from one profile is generally not sufficient to reliably classify a Ground Moving Target Indicator (GMTI) target. When multiple looks are correctly combined, classification accuracy can improve dramatically. At X-band, HRR profiles of typical ground vehicles decorrelate for aspect angle changes greater than 0.1 degree, thus, all looks in a practical system are independent. From the ATR perspective, the challenge is one of correctly associating HRR profiles from one look to the next. If the problem is examined from the opposite point of view, the ATR evidence can greatly improve the association accuracy of a tracker above and beyond that of kinematics. This ATR information assists tracking in regimes of high traffic density or low revisit rates through better association of the high-value targets from one epoch to the next. In this paper, we present a new HRR-aided tracker. The performance of this tracker will be characterized in a simulation and compared to the performance of a purely kinematic tracker. These results show that HRR-aided tracking can tolerate at least an order of magnitude higher traffic density than trackers functioning on kinematics alone. This improvement in performance is reduced, but not eliminated, if the additional radar resources for HRR are considered.