Sustainable Autonomous Target Recognition of Maritime Targets from Passive ISAR Imagery

The RDRTec team proposes to study the feasibility of innovative approaches for bistatic Inverse Synthetic Aperture Radar (ISAR) imaging to provide robust, efficient, sustainable, and high performance target recognition capabilities to operators using multistatic ISAR images. This includes techniques for optimally combining the information and features from monostatic ISAR with multi-static ISAR images and incorporating them into Maritime Classification Aids (MCA) and radar Resource Manager (RM) that are currently transitioning to naval surveillance radars. Multi-static imaging has both challenges and opportunities. Besides the advantage of covert receiver platforms , additional opportunities include diverse illumination and viewing geometries expanding the information degrees of freedom that can provide richer information for target identification. Unique differences in scattering as a function of bistatic angle may be used as discriminating features and target pose angles can be estimated.