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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. Highly-Scalable Computational-Based Engineering Algorithms for Emerging Parallel Machine Architectures

    SBC: RNET TECHNOLOGIES INC            Topic: AF10BT13

    ABSTRACT: RNET and The Ohio State University propose to use algorithmic modifications and multi-level parallelization techniques and tools to improve the scalability of the aero-line/aero-elastic coupled CFD/CSD codes relevant to the DoD/AF (e.g., CREATE/Kestrel). The optimizations will address inter-node and intra-node parallelization to better target emerging compute architectures (e.g., multi ...

    STTR Phase II 2013 Department of DefenseAir Force
  2. Space-based Passive Night Vision Vibrometer

    SBC: Wavefront            Topic: AF12BT02

    ABSTRACT: Remote sensing of surface vibration is an important modality of measures and signals intelligence (MASINT) with a wide range of military applications including target discrimination, clutter rejection, analysis of engine signatures, and seismic detection of buried threats. Other applications of remote vibrometry include remote acoustic sensing, aerial sonar, structural damage assessmen ...

    STTR Phase I 2013 Department of DefenseAir Force
  3. Scalable Adaptive Fiber-Array Elements (SAFARE) for Directed Energy Phased Arrays

    SBC: MV INNOVATIVE TECHNOLOGIES, LLC            Topic: AF12BT13

    ABSTRACT: To address the Air Force need for an adaptive optics system using a fiber laser array as the spatial phase correction system within the subaperature of an array of discrete telescopes, Optonicus and The University of Dayton propose the development of a new Scalable Adaptive Fiber-Array Elements (SAFARE) system. The integration of new fiber-array architectures with novel imaging and ada ...

    STTR Phase I 2013 Department of DefenseAir Force
  4. Directionally-Tailored Infrared Emission and/or Transmission

    SBC: Sensormetrix INC            Topic: AF10BT30

    ABSTRACT: It is proposed to demonstrate a surface fabricated using thin film metamaterial designs that can exhibit rapidly varying angular as well as spectral emissivity profiles. The technology enables specification of desired angular pattern at design time, and can be fabricated in large area formats. BENEFIT: The proposed technology will allow directional control of thermal radiation in app ...

    STTR Phase II 2013 Department of DefenseAir Force
  5. Real-time Location of Targets in Cluttered Environments

    SBC: MATHEMATICAL SYSTEMS & SOLUTIONS, INC.            Topic: AF12BT05

    ABSTRACT: We propose development of an efficient physics-based computational capability for real-time radar location of targets in cluttered environments. Our effort will focus, in particular, on air traffic targets in static natural environments that include dynamic effects such as spinning wind turbines. The proposed methodology models radar signal scattering in cluttered environments on t ...

    STTR Phase I 2013 Department of DefenseAir Force
  6. Scaled Transonic Dynamic Aeroelasticity Through Wind Tunnel Testing (ST-DAWTT)

    SBC: CREATIVE AERO ENGINEERING SOLUTIONS INC.            Topic: AF12BT12

    ABSTRACT: Under this collaborative effort, Creative Aero Engineering Solutions (CAES) and its academic partner University of California Los Angeles (UCLA) are pleased to team on the research entitled"Scaled Transonic Dynamic Aeroelasticity through Wind Tunnel Testing (ST-DAWTT),"consisting of a novel approach for characterizing the transonic aeroelastic environment of a full-scale fighter in the ...

    STTR Phase I 2013 Department of DefenseAir Force
  7. Biomimetic Integrated Optical Sensor Systems

    SBC: Luminit LLC            Topic: AF12BT03

    ABSTRACT: To address the Air Force"s need for a novel advanced imaging sensor concept that samples all of the information in the radiation field, taking inspiration from biological systems, Luminit proposes to develop a new Biomimetic Integrated Optical Sensor (BIOS) system. The system will be based on the unique integration of a wide field-of-view (FOV) miniature staring multi-aperture compound ...

    STTR Phase I 2013 Department of DefenseAir Force
  8. Development of a Rapidly Deployable Scaled Fighter for Aeroelastic Research

    SBC: MAINSTREAM ENGINEERING CORP            Topic: AF12BT12

    ABSTRACT: Experimental testing of dynamic models has been performed for more than 50 years and a wealth of data exists for individual models. However, this data is often either restricted as proprietary or is not suitable for CSE tool validation as a result of incomplete model or test information. Mainstream Engineering proposes to design, fabricate, and test a scaled fighter for aeroelastic ...

    STTR Phase I 2013 Department of DefenseAir Force
  9. Biologically-inspired Integrated Vision System

    SBC: SPECTRAL IMAGING LABORATORY            Topic: AF12BT03

    ABSTRACT: The U.S. Air Force has a need to develop a new class of advanced, wide field of view (WFOV) imaging sensors that sample the radiation field in multiple modes: spectral, temporal, polarization, and detailed object shape. These multimodal sensors are to be deployed on high altitude drones to enhance their intelligence, surveillance, and reconnaissance (ISR) capabilities. Smaller versio ...

    STTR Phase I 2013 Department of DefenseAir Force
  10. Innovations in Physical Modeling and Statistical Exploitation of Electromagnetic Target Signatures

    SBC: Five Focal LLC            Topic: AF12BT06

    ABSTRACT: Feature extraction and target recognition suffer from a lack of a reliable model for both exploitable target features and the electromagnetic signature they possess. Signature data are often hard to interpret and invert to recover the target robustly. Bayesian learning approaches to statistical pattern recognition are based on the use of training sets of inputs and outputs, a data mode ...

    STTR Phase I 2013 Department of DefenseAir Force
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