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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. Smart Isolation Mounts for Airborne Guns (SIMAG)

    SBC: QUALITY RESEARCH, DEVELOPMENT & CONSULTING, INC.            Topic: N/A

    Not Available With the advent of quieter threats and the shift in operational emphasis from deep-ocean to literal areas future airborne ASW systems will increasingly rely on acoustic-receiving buoys with increased spatial discrimination to combat increased ambient noise, reverberation and multi-path effects. The implication is that signal detection and classification must now be performed on the ...

    SBIR Phase I 1999 Department of DefenseArmy
  2. An Asynchronous Testbed for Low Power DSPs

    SBC: THESUS LOGIC, INC.            Topic: N/A

    Not Available SBIR N99-102, Automated Test & Integation Methods for COTS Hardware & Software Components, seeks an innovative approach to testing COTS using a Hot Box or alternative concept for pre-integration testing. The solution is expected to: 1. Reduce logistics material and testing associated with Combat System supportability. 2. Result in a significant cost and time savings to the Navy lo ...

    SBIR Phase I 1999 Department of DefenseArmy
  3. Secure, Compressed Multimedia Data over Variable Bit Rate, ATM Adaptation Layer (AAL) Algorithm

    SBC: ARCHITECTURE TECHNOLOGY INC            Topic: N/A

    Not Available Missile defense systems rely heavily on plume signature recognition to help identify and neutralize hostile missiles. Unfortunately, plume signature modeling has proven to be extremely difficult, with modelers struggling to obtain good agreement between predictions and data. The modeled exhaust conditions display a significant lack of fidelity as compared to the actual constituents ...

    SBIR Phase I 1999 Department of DefenseArmy
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