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2005

Research and Development . 2011. 2010. 2006. 2007. 2008. 2004. 2005. 2009. AOSN-II. Adaptive Sampling and Prediction (ASAP). Autonomous Wide Aperture Cluster for Surveillance (AWACS). Undersea Persistent Surveillance (UPS) . Persistent Littoral Undersea Surveillance (PLUS).

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2005

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  1. Research and Development 2011 2010 2006 2007 2008 2004 2005 2009 AOSN-II Adaptive Sampling and Prediction (ASAP) Autonomous Wide Aperture Cluster for Surveillance (AWACS) Undersea Persistent Surveillance (UPS) Persistent Littoral Undersea Surveillance (PLUS) Basic Research Program Exploratory Development Program Advanced Development Program

  2. Needs Ocean Fields with Uncertainty Noise Statistics Signal Cues Environment exploitation algorithms Mobile, adaptive aperture passive arrays Efficient optimization algorithms Mobile, self-focusing passive arrays Convergence optimization Undersea Persistent Surveillance (UPS) Stages Opportunities Stage 0 Ocean Nowcast / Forecast Glider fleet Targeted measurements Data assimilative models Remote Sensing Efficient propagation models Stage I Adaptive Search Vector sensor arrays Efficient intercept algorithms Stage II Adaptive DCLT Advanced signal processing Cooperative behavior Stage III Adaptive Convergence Mobile, network control

  3. Stages 0 and I Key Questions AOSN-II ASAP How to obtain the best field estimates given sparse sampling? What advantage does targeted observation give to predictive skill? What advantage does a clustered, adaptive architecture provide to predictive skill? Environment Feature tracking Objects ….. ….. ….. Target glimpse What advantage does adapting to the environment provide to detection? What advantage does a nested, adaptive aperture antenna provide to detection? What gain advantage do mobile, vector arrays provide? AWACS UPS

  4. In-Situ Data Remote Sensing Data Databases Lagrangian & Fixed sensors Mobile sensors Adaptive Sampling Strategies Data Assimilation External Forcing Models Environment Analysis & Prediction Object Analysis & Prediction Constituent Fields Current fields Biological thin layers Detection, Classification, Localization, Tracking (DCLT) Decision Field Sampling Decision Feedback reduces error

  5. UPS Cornerstones Passive Vector Sensor ArraysE-Field Sensors Acoustic and Ocean ModelsTargeted Observations Directional Sensitivity Adaptive Feedback Mobility, Persistence Autonomous DCLT Autonomous Underwater VehiclesAcoustic Modems Autonomous DCL & Automated Tracking

  6. Example Coverage Analysis for All Gliders in AOSN-II • varies 2 km (at shore) to 10 km (at 4000m depth), t = 24 hours, Outside black contour, locations not sampled for 48 hours.

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