Adaptive single-frame superresolution for detecting closely spaced IR targets in clutter

This paper addresses the problem of individually resolving very closely spaced infrared (IR) point targets in clutter, an important requirement in a variety of applications including air defense, where groups of targets may be operating in close formations, and astronomy, where stars can be closely spaced in angle as seen from the sensor's perspective. Novel linear and nonlinear (order statistic) adaptive noncoherent superresolution spatial-processing methods are introduced and employed to solve this problem using a single frame of IR data.