Compact, High Efficiency IRCM Laser Source

Not Available The goal of this proposal is to improve the figure-of-merit of the focus of attention stage of automatic target recognition (ATR) by developing a novel hierarchical multi-resolution prescreening architecture addressing: (A) new sensory input filtering methods that highlight target discriminating features and discard nonrelevant features; and (B) a more complete characterization of targets, decoys and clutter by modeling both the representations at each scale and across scales by means of learned generative nonlinear models. the combination of improvements (A) and (B) is represented in our Wavelet Pattern Detection (WPD-ATR) approach incorporating the prescreening of input to a nonlinear adaptive system (neural net). The WPR-ATR is designed for ultrahigh resolution sensors/radars - e.g., TeraHertz sensors/radars - and testable either in conjunction with such sensors/radars as a hardware-in-the-loop demonstration of as simulation/emulation on BMDO's VDHTB.