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Award Data

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The Award database is continually updated throughout the year. As a result, data for FY21 is not expected to be complete until September, 2022.

Download all SBIR.gov award data either with award abstracts (290MB) or without award abstracts (65MB). A data dictionary and additional information is located on the Data Resource Page. Files are refreshed monthly.

  1. N/A

    SBC: 21ST CENTURY SYSTEMS, INC.            Topic: N/A

    N/A

    SBIR Phase II 1999 Department of DefenseOffice of the Secretary of Defense
  2. N/A

    SBC: DEUMBRA, INC.            Topic: N/A

    N/A

    SBIR Phase II 1999 Department of DefenseDefense Advanced Research Projects Agency
  3. N/A

    SBC: DEUMBRA, INC.            Topic: N/A

    N/A

    SBIR Phase II 1999 Department of DefenseAir Force
  4. IMPROVED ULTRAFILTERS FOR BIOPROCESSING

    SBC: Abel Company            Topic: N/A

    N/A

    SBIR Phase II 1994 Department of Health and Human Services
  5. ABDUCTIVE/EXPERT SYSTEM CONTROLLER

    SBC: ABTECH CORPORATION            Topic: N/A

    THE OBJECTIVE OF THIS EFFORT IS TO DEMONSTRATE A PROTOTYPE CONTROLLER FOR A HOWITZER USING A HYBRID NETWORK AND PRODUCTION RULE SYSTEM. THE RESULTING ADAPTIVE CONTROLLER WILL DEMONSTRATE THE FEASIBILITY OF DEVELOPING A REVOLUTIONARY CONTROLLER CAPABLE OF ADAPTING IN A DYNAMIC ENVIRONMENT, MONITORING AND DIAGNOSING BEHAVIOR, AND PREDICTING FUTURE FAULTS AND MAINTENANCE REQUIREMENTS. ABTECH HAS DEVE ...

    SBIR Phase II 1994 Department of DefenseArmy
  6. An Ontogenic Polynomial Neural Network/Expert System Modeling Evnironment for Chaotic Avionics Systems Behavior Prediction

    SBC: ABTECH CORPORATION            Topic: N/A

    Ontogenic neural networks, those which automatically discover their topology during synthesis, offer substantial advantages over traditional machine learning techniques. They also have the potential to offer many benefits in several areas of avionics research. Among potential application areas is the ability to predict or forecast the behavior of a seemingly random or chaotic system. This proposal ...

    SBIR Phase II 1994 Department of DefenseAir Force
  7. Automated Target Assessment Development Environment

    SBC: ABTECH CORPORATION            Topic: N/A

    Automated processing of sensor/signal data and other non-sensor information provides substantial force-multiplying benefits. The timely and cost-effective leveraging of these types of information provides a significant advantage over adversaries not possessing comparable information processing capabilities. The intelligent processing of diverse types of data provides a target assessment technology ...

    SBIR Phase II 1996 Department of DefenseDefense Advanced Research Projects Agency
  8. SAR-Based Automatic Target Recognition Avionics System

    SBC: ABTECH CORPORATION            Topic: N/A

    Intelligent processing of battelfield sensor data and other information provides substantial force-multiplying benefits. The timely and cost-effective leveraging of information provides a signficant advantage over adversaries not possessing comparable information processing capabilties. Among these is automatic target recognition (ATR). Under previous and current Federal funding, AbTech has develo ...

    SBIR Phase II 1996 Department of DefenseAir Force
  9. Sensor Fusion through Advanced Computing Techniques

    SBC: ABTECH CORPORATION            Topic: N/A

    AbTech Corporation proposes to apply its unique abductive information modeling (AIMTM) technology to develop a sensor fusion demonstration for command, control, communication, computer and information systems. Phase I is the necessary and sufficient precursor to an operational disparate sensor fusion for C4I applications. Phase I will show the feasibility of using AIM to model sensor data, threats ...

    SBIR Phase II 1997 Department of DefenseNavy
  10. ModelQuest Satellite Telemetry Anomaly Resolution (MQ STAR)

    SBC: ABTECH CORPORATION            Topic: N/A

    This effort will result in the development of a Satellite Telemetry Anomaly Resolution (STAR) tool that automatically: 1) analyzes historical telemetry data, 2) learns expected signal characteristics for specific telemetry signals using prediction networks¿ (an advanced statistical modeling approach) and innovative case based reasoning (CBR) techniques, and 3) applies these models to detect and ...

    SBIR Phase II 1997 Department of DefenseAir Force
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