You are here

Award Data

For best search results, use the search terms first and then apply the filters
Reset

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. Neurofeedback Training and Hyperscanning for Mission Readiness and Return-to-Duty via Functional Near-Infrared Spectrometry (fNIRS)

    SBC: SOAR TECHNOLOGY INC            Topic: DHA19B001

    Until now,much of theresearch usingfunctional near-infrared spectroscopy (fNIRS) has focused on tailoringasystem to detect onlyafew cognitivestatesand theapplication of theseapproaches outsidethe laboratory is not well tested. This solution provides severely limited coverage of thespacethat this technology could beapplied to,and is notarealistic path for developing neuroimagingasan operational ass ...

    STTR Phase I 2020 Department of DefenseDefense Health Agency
  2. TeraNet – A Wideband Terahertz Communication Network

    SBC: Intelligent Automation, Inc.            Topic: AF19BT008

    Terahertz communication is anticipated to provide ultra-high capacity links up to 1Tbps. Thus, Terahertz communication is promising to support wide varieties of emerging high throughput and low latency applications, including military applications. However, the Terahertz channel suffers from severe path loss and is highly sensitive to obstacles. Hence, novel solutions should be designed to account ...

    STTR Phase I 2020 Department of DefenseAir Force
  3. Multiband Equipment for Spectrum Agility (MESA)

    SBC: FIRST RF CORPORATION            Topic: AF19BT009

    In this Phase I STTR program, FIRST RF and GMU will investigate the interrelated trades of directional antenna hardware capabilities and the operational advantages of spectrum agility for airborne networking. GMU’s modeling and simulation (M&S) capabilities combined with the FIRST RF expertise in advanced antenna hardware will provide Air Force with a powerful team to understand the advanta ...

    STTR Phase I 2020 Department of DefenseAir Force
  4. Test Rig for Effective Reproduction of Inlet Distorted Supersonic Flows

    SBC: CFD RESEARCH CORPORATION            Topic: AF19BT012

    The subsonic diffuser duct of a modern tactical aircraft is the most difficult component to verify performance at off-design conditions, because of the large cost of testing/modeling complete installations at large scale. It is desirable to effectively reproduce the flow at the end of a supersonic inlet for interfacing with a direct-connect subsonic duct rig. The CFDRC team proposes to deliver a r ...

    STTR Phase I 2020 Department of DefenseAir Force
  5. Optimized Substrate Orientation for 4H-SiC Epitaxy

    SBC: MAINSTREAM ENGINEERING CORP            Topic: AF19BT015

    SiC devices are limited in application due to high substrate manufacturing costs. High temperatures are required to make high quality 4H-SiC substrates, limiting throughput and imposing large maintenance costs on equipment. Lowering the process temperature will make SiC devices more economical, but difficulties with maintaining useful growth rates remain; altering CVD gas precursor chemistry alone ...

    STTR Phase I 2020 Department of DefenseAir Force
  6. Machine Learning based Domain Adaptation (MLB-DA) for Multiple Source Classification and Fusion

    SBC: INTELLIGENT FUSION TECHNOLOGY, INC.            Topic: AF19CT002

    Generalizing models learned on one domain to novel domains has been a major obstacle in the quest for universe object recognition. The performance of the learned models degrades significantly when testing on novel domains due to the presence of domain shift. In this proposal, we aim to develop a deep learning-based multi-source self-correcting approach to fuse data with different modalities at the ...

    STTR Phase I 2020 Department of DefenseAir Force
  7. Deep Transfer Learning Across Domains, Modalities and Classes

    SBC: INTELLIGENT FUSION TECHNOLOGY, INC.            Topic: AF19CT004

    The capability of “transferring” learned classifiers from one domain, or set of targets, to classify different targets or the same targets but in different domains is of great interest to the United States Air Force. It is an enabling technology for the USAF to build Aided Target Recognition and other algorithms for environments and targets where the data or labeled data is scarce. In ...

    STTR Phase I 2020 Department of DefenseAir Force
  8. Human Behavior Analytics Tool (HBAT)

    SBC: INTELLIGENESIS LLC            Topic: AF19CT007

    IntelliGenesis seeks to lower the incidence of military personnel and veteran suicide through innovative machine learning and data science approaches applied to military personnel data. Our developers, engineers, and analysts, in coordination with university subject matter experts, will collaborate to design and develop an analytic system capable of ingesting and normalizing personnel (non-medical ...

    STTR Phase I 2020 Department of DefenseAir Force
  9. SmartWavAudit: smart technologies for electrical waveform auditing

    SBC: Intelligent Automation, Inc.            Topic: AF19CT009

    Reliability of power generators, distribution systems and motors are essential in ensuring the efficient and reliable operation of industrial manufacturing systems. However, different types of machine health threats (fault or attack) may occur. There may be direct or inderict attacks and different types of short circuit faults for the electric devices such as single phase faults, phase to phase fa ...

    STTR Phase I 2020 Department of DefenseAir Force
  10. Protecting Fingerprint Systems from Spoof Attacks (PFSSA)

    SBC: OMBRA LLC            Topic: AF19CT010

    Ombra, a Florida-based Service-Disabled Veteran Owned Small Business (SDVOSB) will conduct a thorough Feasibility Study to develop a Protecting Fingerprint Systems from Spoof Attacks (PFSSA) system for the Air Force and United States Special Operation Command (USSOCOM). Biometric systems are vulnerable to attacks using fake biometrics to obscure an individual’s natural biometric signature. ...

    STTR Phase I 2020 Department of DefenseAir Force
US Flag An Official Website of the United States Government