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Award Data

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The Award database is continually updated throughout the year. As a result, data for FY24 is not expected to be complete until March, 2025.

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.

The SBIR.gov award data files now contain the required fields to calculate award timeliness for individual awards or for an agency or branch. Additional information on calculating award timeliness is available on the Data Resource Page.

  1. N/A

    SBC: Electron Power Systems, Inc.            Topic: N/A

    N/A

    STTR Phase I 1999 Department of DefenseMissile Defense Agency
  2. N/A

    SBC: Electron Power Systems, Inc.            Topic: N/A

    N/A

    STTR Phase II 1999 Department of DefenseMissile Defense Agency
  3. New Rare-Earth-Doped Glass Fiber Lasers and Amplifiers for 1.54 um Communications

    SBC: KIGRE, INC.            Topic: N/A

    N/A

    STTR Phase I 1999 Department of DefenseMissile Defense Agency
  4. Novel AlGaN/GaN Heterojunction Bipolar Transistor with Enhanced p-type Doped Base

    SBC: NZ APPLIED TECHNOLOGIES CORP.            Topic: N/A

    N/A

    STTR Phase I 1999 Department of DefenseMissile Defense Agency
  5. Radiation Hard, Nonvalatile Magnetic RAM Using Novel Magnetic Tunneling-Junction Device on Silicon Semiconductor

    SBC: Spinix Corporation            Topic: N/A

    N/A

    STTR Phase I 1999 Department of DefenseMissile Defense Agency
  6. High-Speed Three-Channel Photonic Time Delay Unit

    SBC: AGILTRON, INC.            Topic: MDA08T012

    An innovative, super-miniature, fast-switching array-based photonic time delay device is being developed for the active electronically scanned-array (AESA) MDA and Navy radars. The design is based on the fast electro-optic effect, the super miniature fiber-lens collimation array, and the existing WDM photonic true time delay technologies. In Phase I Agiltron has successfully demonstrated the core ...

    STTR Phase II 2011 Department of DefenseMissile Defense Agency
  7. Real-Time Health Management Portable Sensor for Solid Rocket Motors

    SBC: PHYSICAL SCIENCES INC.            Topic: MDA14T004

    Physical Sciences Inc. (PSI) proposes to design, develop, and demonstrate a portable, non-invasive, real-time sensor to assess the chemical and physical health of solid rocket motors (SRMs) as a function of age without affecting the motors integrity. In Phase I, a sensor to monitor specific gas species that are markers of the chemical and mechanical aging processes of composite and double base pr ...

    STTR Phase I 2015 Department of DefenseMissile Defense Agency
  8. Adaptive Management and Mitigation of Uncertainty in Fusion (AMMUF)

    SBC: CHARLES RIVER ANALYTICS, INC.            Topic: MDA13T001

    In our Adaptive Management and Mitigation of Uncertainty in Fusion (AMMUF) project, we will model the entire multi-sensor fusion process as a probabilistic model and reason about the different design and algorithmic decisions that can be made by system engineers. This fusion model will use standard fusion system representations and ideas from statistical relational learning field to create flexibl ...

    STTR Phase II 2015 Department of DefenseMissile Defense Agency
  9. Uncertainty Characterization Using Copulas (UC)2

    SBC: BOSTON FUSION CORP            Topic: MDA13T001

    Boston Fusion, together with our teammate Syracuse University, propose a program of research and development, Uncertainty Characterization Using Copulas (UC)2, that will result in a parametric framework based on the statistical theory of copulas for modeling uncertainties for the problem of object classification. (UC)2 will produce a mathematical framework, founded on rigorous theoretical analysis ...

    STTR Phase II 2015 Department of DefenseMissile Defense Agency
  10. Deep Inference and Fusion Framework Utilizing Supporting Evidence (DIFFUSE)

    SBC: BOSTON FUSION CORP            Topic: MDA15T001

    Combining information from disparate sensors can lead to better situational awareness and improved inference performance; unfortunately, traditional multi-sensor fusion cannot capture complex dependencies among different objects in a scene, nor can it exploit context to further boost performance. Integrating context information within a fusion architecture to reason cohesively about scenes of inte ...

    STTR Phase I 2016 Department of DefenseMissile Defense Agency
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