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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. 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
  2. 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
  3. 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
  4. 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
  5. Rapid Discovery of Evasive Satellite Behaviors

    SBC: DATA FUSION & NEURAL NETWORKS, LLC            Topic: AF17CT02

    The DF&NN team has significant experience in delivering Space Domain Awareness tools. These tools will be applied to 2 years of GEO ephemeris data of active satellites at DF&NN. The RDESB prototype will reduce the risk in rapidly discovering the behavioral patterns of potentially evasive and/or ambiguous active resident space objects. RDESB will detect non-Keplerian behavior in ephemeris data for ...

    STTR Phase I 2018 Department of DefenseAir Force
  6. Adaptive Markov Inference Game Optimization (AMIGO) for Rapid Discovery of Evasive Satellite Behaviors

    SBC: INTELLIGENT FUSION TECHNOLOGY, INC.            Topic: AF17CT02

    Space superiority requires space protection and space situational awareness (SSA), which rely on rapid and accurate space object behavioral and operational intent discovery. The focus of this project is to develop a stochastic approach for rapid discovery of evasive satellite behaviors. Designing the innovative decision support tool has numerous challenges: (i) partial observable actions; (ii) eva ...

    STTR Phase I 2018 Department of DefenseAir Force
  7. Verification and Validation of Algorithms for Resilient Complex Software Controlled Systems

    SBC: APPLIED DEFENSE SOLUTIONS, INC.            Topic: AF17CT05

    In response to the challenges described in AF173-CT05, Applied Defense Solutions (ADS) and the University of New Mexico (UNM) (equivalently, the ADS Team) propose to research and develop innovative validation and verification (V&V) algorithms for spacecraft GN&C. The ADS Team is unique in that it brings operational flight GN&C software experience (ADS) with cutting edge research on algorithm V&V ( ...

    STTR Phase I 2018 Department of DefenseAir Force
  8. Rydberg-atom RF Sensors for Direction Finding and Geolocation

    SBC: COLDQUANTA, INC.            Topic: AF17AT028

    ColdQuanta is partnering with Dr. Zoya Popovic at the University of Colorado, Boulder, to develop a three-dimensional quantum-enhanced radio-frequency (RF) signal sensor and direction finder. Our approach combine Rydberg-atom-based RF electrometry and discrete lens arrays (DLAs) of planar antennas. The DLA will serve as a Fourier optic for an incident wave, and a Rydberg-atom RF electrometer will ...

    STTR Phase I 2018 Department of DefenseAir Force
  9. Disposal of Aqueous Film-Forming Foam using Hydrodynamic Cavitation

    SBC: DYNAFLOW, INC.            Topic: AF17BT001

    The widespread use of Aqueous Film Forming Foams (AFFF) at DOD facilities for firefighting, training, and fire suppression systems has resulted in numerous contamination sites. The perfluoroalkyl (PFA) compounds used in the AFFF, such as perfluoroalkyl sulfonates (PFOS) and perfluoroalkyl carboxylic acids (PFOA) are extremely stable in the environment and have been shown to be resistant to typical ...

    STTR Phase I 2018 Department of DefenseAir Force
  10. Closed-Loop Feedback Control for Transcranial Direct Current Stimulation

    SBC: QUANTUM APPLIED SCIENCE & RESEARCH INC            Topic: AF17BT002

    Because of rising demand for human analysts and more efficient processing of increasingly large and challenging amounts of intelligence, human limitations on mental workload, cognitive fatigue, and attentionor task engagement, need to be accurately monitored in real-time in order to provide sensitive detection of impaired cognitive states. It is a challenge to continuously monitor these cognitive ...

    STTR Phase I 2018 Department of DefenseAir Force
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