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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. Directional Cross-Layer Networking Solution

    SBC: FUSE INTEGRATION, INC.            Topic: AF17BT003

    Currently networks are not taking advantage of the inherent benefits of high multi-beam directional networking. For example, the current MADL implementation simply daisy chains the nodes in the network creating multiple single points of network failure (of course retaining self-healing properties.) The Fuse Directional Cross-Layer Networking Solution (DCLNS) optimized architecture features a robus ...

    STTR Phase I 2018 Department of DefenseAir Force
  2. 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
  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. Electrically Small Multiferroic Antennas

    SBC: SA PHOTONICS, LLC            Topic: AF14AT12

    ABSTRACT: We exploit recent advances in magnetoelectric/piezoelectric (ME/PE) composite materials to enable the development of efficient sub-wavelength radio frequency (RF) transmitting antennas. With these materials will be possible to achieve high dielectric permittivity and magnetic permeability, slow electromagnetic propagation and low RF loss tangents. Together, these special properties m ...

    STTR Phase I 2015 Department of DefenseAir Force
  5. Embedded Sensors for Flight Test (Every Aircraft a Test Aircraft)

    SBC: NEXTGEN AERONAUTICS, INC.            Topic: AF14AT01

    ABSTRACT: Two accelerating trends in military aircraft design and development are apparent: (1) increasing system capabilities in terms of weapon systems, ISR payloads, guidance, navigation and control (GNC), etc., enabled by ever-smaller and evermore capable electronics; and (2) reduction in overall size and available space for auxiliary equipment (and associated wiring, etc.) to measure and asse ...

    STTR Phase I 2015 Department of DefenseAir Force
  6. Embedded Sensors for Flight Test (Every Aircraft a Test Aircraft)

    SBC: NEXTGEN AERONAUTICS, INC.            Topic: AF14AT01

    Increasing system capabilities in terms of weapon systems, ISR payloads, GNC, etc., enabled by smaller and more capable electronics systems have led to a trend for overall size reduction in military aircraft. This has resulted in a reduction in the avail...

    STTR Phase II 2016 Department of DefenseAir Force
  7. Enabling Moving Target Hand-off in GPS-Denied Environments

    SBC: Systems & Technology Research LLC            Topic: AF15AT34

    ABSTRACT: Future conflicts in contested environments will require coordination between teams of manned and unmanned platforms performing ISR tasks. Coordinating ISR tasks is much more challenging in these contested conditions as GPS cannot be reliably depended upon. Consider the ISR task of handing off a tracked target from one platform to another. Reliably performing this task requires at a mini ...

    STTR Phase I 2015 Department of DefenseAir Force
  8. Enhanced Text Analytics Using Lifted Probabilistic Inference Algorithms

    SBC: Longview International Inc.            Topic: AF13AT11

    ABSTRACT: LVI proposes developing an advanced framework of lifted probabilistic inference algorithms for enhancing the scaling and accuracy of text analytics. In Phase I, LVI explored the scalability of various lifted inference techniques for utilizing Markov Logic Networks (MLN) in the Tuffy software package. Phase I also included investigation and demonstration of DeepDive, a scalable, high-per ...

    STTR Phase II 2015 Department of DefenseAir Force
  9. Enhancing Motion Imagery Classifiers By Principal Component Feature Clustering

    SBC: LONGSHORTWAY INC.            Topic: AF15AT35

    ABSTRACT: LongShortWay Inc and NorthEastern University propose new feature clustering methods that improve performance of motion imagery classifiers. Developed algorithms will be demonstrated on AFRL Minor Area Motion Imagery (MAMI) data; BENEFIT: Enhanced classifier performance, robust feature selection

    STTR Phase I 2015 Department of DefenseAir Force
  10. 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
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