ISAR-based Target Identification with Real and Synthetic Bandwidths

ABSTRACT: This work addresses the feasibility of NCTI in a dynamic urban environment with moving targets to improve track fidelity through challenging scenarios. Unlike many previous NCTI efforts, this classification will not depend on a vast database of signature templates but previous measurements. The research will use crossrange scale invariant features to identify the vehicles due to the limitations of ISAR image formation and quantify the variability of these features between subsequent looks of a vehicle. In addition, the research will address the constraints of ISAR image formation derived from synthetic bandwidth based range profiles. BENEFIT: This research will provide the GOTCHA system with signature aids to the tracking of moving targets as well as the feasibility of ISAR image formation derived from synthetic bandwidth range profiles.