Cognitive Radar Scheduler Architecture

A key feature of any cognitive radar is its ability to make “intelligent” decisions regarding the high-speed allocation of radar resources including energy, waveforms, beamwidth, look angles, timelines, and compute resources. In this paper, a radar scheduler and resource optimization architecture are developed and integrated into a high-fidelity RF modeling and simulation (e.g., RFView) framework to facilitate the assessment of its efficacy for a variety of challenging applications. Results demonstrate the scheduler to prioritize looks and tasks to support wide-area search, probing, and synthetic aperture radar (SAR) collection.