ISOLATION AND PROFILING OF CIRCULATING PC CELLS IN BLOOD

Not Available AETC Inc. proposes to develop and demonstrate clutter rejection algorithms for airborne active ASW systems operating in high clutter environments. These algorithms will exploit nonlinear dynamics to cancel clutter and leave desired target echoes largely undisturbed, significantly increasing the probability of detection and reducing the probability of false alarms. Recent research has shown that modeling radar clutter as the output of a nonlinear system allows the receiver to successfully distinguish between clutter and target echo. Such nonlinear clutter cancelers have been implemented as hidden Markov models, nonlinear Kalman filters and neural networks. All methods take advantage of the fact that-in contrast to completely random noise-clutter is a low-order chaotic signal that can be predicted, if for only for a short time horizon. One experiment using this approach to extract acoustic signals from chaotic clutter reported a 27dB increase in signal-to-clutter ratio. Investigation by AETC Inc. has shown that active sonar reverberation and clutter also display these low-order nonlinear dynamics which are amenable to modeling and cancellation. AETC Inc. proposes to adapt these breakthroughs in radar processing to develop nonlinear clutter canceling algorithms for active sonobuoy use and demonstrate their effectiveness using recorded sea test data.