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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. Environmentally-Compliant Kinetic Metallization Coating Materials for Corrosion and Wear Protection of Military Aircraft and Weapon Systems

    SBC: INNOVATIVE TECHNOLOGY INC            Topic: AF15AT31

    Coating materials and coating methods used to protect U.S. military aircraft and weapon systems from corrosion and wear are in need of environmentally benign alternatives in order to keep up with dynamic regulations associated with environment, safety, and occupational health. Thus, the Air Force is supporting research to develop alternatives to the dangerous materials identified on the OSD Emergi ...

    STTR Phase II 2016 Department of DefenseAir Force
  2. Broad Spectrum Optical Property Characterization

    SBC: SPECTRAL MOLECULAR IMAGING, INC.            Topic: AF15AT12

    Liquid Crystal Arrayed Microcavities (LCAM) are a new hyperspectral technology initiated by collaboration among Spectral Molecular Imaging, Advanced Microcavity Sensors and Montana State University Spectrum Laboratory.At the core of this revolutionary technology lie picoliter volume optical cavities that exploit liquid crystal birefringence for tuning an effective cavity length.During a Phase I on ...

    STTR Phase II 2016 Department of DefenseAir Force
  3. DREAMIT- Design, Reconfigure and Evaluate Autonomous Models in Training

    SBC: TIER 1 PERFORMANCE SOLUTIONS LLC            Topic: AF15AT14

    Our Phase I work focused on improving modeling and simulations so that the impact of autonomous systems in the battlespace could be better understood. As we have trained our attention on Phase II, it has become increasingly clear that the work we are doing to improve the modeling and simulation of autonomous systems also provides significant leverage for the development of the intelligent behavior ...

    STTR Phase II 2016 Department of DefenseAir Force
  4. Reverberation Mitigation of Speech

    SBC: MINERVA SYSTEMS & TECHNOLOGIES LLC            Topic: AF15AT17

    Automatic speech recognition (ASR) technology is in wide use today and has been successfully integrated into a number of applications. Although there are also many potential applications for automatic speaker identification (SID), SID accuracy rates are generally not sufficient for widespread use in practical applications. For high accuracy ASR and SID, the microphone must be located near the talk ...

    STTR Phase II 2016 Department of DefenseAir Force
  5. Plasma Generator for Controlled Enhancement of the Ionosphere

    SBC: Enig Associates, Inc.            Topic: AF15AT22

    Enig Associates, Inc., a small business providing advanced modeling and simulation capabilities to the DoD and DoE, is proposing an innovative and novel electrical approach, using explosive-driven flux compression generators to Joule heat light metal load in sub millisecond time scale from a solid metal state to a first ionization plasma state going through multi-phase transitions to generate an a ...

    STTR Phase II 2016 Department of DefenseAir Force
  6. ROBUST MOVING TARGET HANDOFF IN GPS-DENIED ENVIRONMENTS

    SBC: UTOPIACOMPRESSION,CORPORATION            Topic: AF15AT34

    Unmanned aircraft systems (UAS) are increasingly seen as a cornerstone in developing the future Defense infrastructure and it is critical that they collaborate efficiently and execute complex missions in denied environments. Although great progress has been made in GPS-denied navigation, the target handoff problem in GPS-denied environments has not been extensively studied. In this problem, a trac ...

    STTR Phase II 2016 Department of DefenseAir Force
  7. Small Sample Size Semi-Supervised Feature Clustering for Detection and Classification of Objects and Activities in Still and Motion Multi-spectral Imagery

    SBC: TOYON RESEARCH CORPORATION            Topic: AF15AT35

    Toyon Research Corp. and the Penn State Univ. propose research and development of innovative algorithms for classifying objects and activities observed in high-dimensional data extracted from multi-sensor motion imagery. The proposed algorithms include novel feature clustering techniques to enable effective characterization of intra-class and inter-class appearance variations in datasets containin ...

    STTR Phase II 2016 Department of DefenseAir Force
  8. ENHANCING MOTION IMAGERY CLASSIFIERS BY PRINCIPAL COMPONENT FEATURE CLUSTERING

    SBC: LONGSHORTWAY INC.            Topic: AF15AT35

    LongShortWay Inc. and Northeastern University propose a family of feature reduction and ensemble classifier methods based on Principal Component and Dynamic Logic feature clustering algorithms. New methods combine feature clustering with non-linear feature reduction via manifold learning, and bagging, boosting, and stacking ensemble algorithms.

    STTR Phase II 2016 Department of DefenseAir Force
  9. Sun-Tracking Millimeter Wave Radiometer

    SBC: PROSENSING INC.            Topic: AF17CT01

    This Phase I STTR proposal describes the development of a dual frequency millimeter-wave sun tracking radiometer designed to measure total atmospheric attenuation from ground level to the top of the atmosphere.The suns brightness temperature, which is on the order of 10,000K at millimeter-wavelengths, provides an ideal background reference allowing high dynamic range estimation of total atmospheri ...

    STTR Phase I 2018 Department of DefenseAir Force
  10. Rapid Discovery of Evasive Satellite Behaviors

    SBC: APPLIED DEFENSE SOLUTIONS, INC.            Topic: AF17CT02

    This is a prototype system that will take raw observation data, detect and characterize maneuvers, and use reinforcement learning to understand and react to evasive RSO behaviors in near real time. This will provide a framework to evaluate autonomous behavior strategies, such a safety, effectiveness, and robustness to manipulation. This work will enable surveillance operators to distinguish betwee ...

    STTR Phase I 2018 Department of DefenseAir Force
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