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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. Blended Reality Solution for Live, Virtual, and Constructive Field Training

    SBC: SA PHOTONICS, LLC            Topic: AF17AT011

    A Battlefield Airman (BA) has one of the most challenging positions in the military. BA personnel are tasked with the dual roles of being warfighters as well as Combat Controllers, Pararescuemen, Tactical Air Control Party (TACP) members and Special Operations Weather Technicians often while behind enemy lines. These complex duties require high fidelity training. In some cases, such as Pararescuem ...

    STTR Phase II 2018 Department of DefenseAir Force
  2. Hybrid DNN-based Transfer Learning and CNN-based Supervised Learning for Object Recognition in Multi-modal Infrared Imagery

    SBC: TOYON RESEARCH CORPORATION            Topic: 1

    On this effort Toyon Research Corp. and The Pennsylvania State University are developing deep learning-based algorithms for object recognition and new class discovery in look-down infrared (IR) imagery. Our approach involves the development of a hybrid classifier that exploits both transfer learning and semi-supervised paradigms in order to maintain good generalization accuracy, especially when li ...

    STTR Phase I 2018 Department of DefenseNational Geospatial-Intelligence Agency
  3. Algorithms for Look-down Infrared Target Exploitation

    SBC: SIGNATURE RESEARCH, INC.            Topic: 1

    Signature Research, Inc. (SGR) and Michigan Technological University (MTU) propose a Phase I STTR effort to develop a learning algorithm which exploits the spatio-spectral characteristics inherent within IR imagery and motion imagery.Our archive of modelled and labeled data sets will allow our team to thoroughly capture the variable elements that will drive machine learning performance.The overall ...

    STTR Phase I 2018 Department of DefenseNational Geospatial-Intelligence Agency
  4. Volume Digital Holographic Wavefront Sensor

    SBC: NUTRONICS, INC.            Topic: AF18AT006

    Nutronics, Inc. and Montana State University propose to develop and evaluate computational methods for a Volume Digital Holographic Wavefront Sensor (VDHWFS).VDHWFS based imaging offers the potential to provide the equivalent of wide field of view adaptive optics (AO) compensated imaging, but without the added complexity of AO components and hardware.Recent result for coherent imaging developed by ...

    STTR Phase I 2018 Department of DefenseAir Force
  5. Non-Linear Adaptive Optics (NLAO)

    SBC: NUTRONICS, INC.            Topic: AF18AT008

    Nutronics, Inc. and Montana State University propose to develop an approach for non-linear control of hysteresis and incorporate (if necessary) integrated Multi-Input-Multi-Output real time control with this capability.Our control systems already include a proven high speed real time control approach to determine the optimal set of actuator commands that satisfy inter-actuator stroke limitations.O ...

    STTR Phase I 2018 Department of DefenseAir Force
  6. Stable High Bandwidth AO Control with physical DM constraints

    SBC: Guidestar Optical Systems, Inc.            Topic: AF18AT008

    Adaptive optics (AO) system performance is hindered by the mechanical limits of the deformable mirror (DM), namely stroke limits, interactuator stroke limits, and mechanical resonance.The nature of the multi-in multi-out (MIMO) control system does not lend itself well to notch filters to combat the mechanical resonances, and the stroke limits introduce non-linearities to the system.The traditional ...

    STTR Phase I 2018 Department of DefenseAir Force
  7. Rydberg-atom RF Sensors for Direction Finding and Geolocation (RADARS)

    SBC: COLDQUANTA, INC.            Topic: AF17AT028

    ColdQuanta, in partnership with Dr. Zoya Popovic at the University of Colorado at Boulder, proposes to develop a three-dimensional quantum-enhanced radio-frequency (RF) signal sensor and direction finder. Our approach combines 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 elec ...

    STTR Phase II 2018 Department of DefenseAir Force
  8. Detection of Radio Frequency and Magnetic Field Bioeffects in Living Cells

    SBC: QUINC.TECH INC.            Topic: AF18AT001

    The Biomagnetics Micro Dosimetry System (BMDS) program will design, model, and simulate a microdosimetry system that can measure and create a three dimensional map of weak radiofrequency signals in biological organisms. The heart of the BMDS project is the front end called a Quinc, that delivers very sensitive, broad band measurements with high spatial resolution.The Quinc based front end is a val ...

    STTR Phase I 2018 Department of DefenseAir Force
  9. Volumetric Wavefront Sensing for the Characterization of Distributed-Volume Aberrations

    SBC: Guidestar Optical Systems, Inc.            Topic: AF18AT006

    Modern Directed Energy (DE) missions require target engagements at low elevation angles and long ranges.These engagement geometries require propagation through distributed-volume turbulence. To correct for distributed-volume turbulence effects, an estimation of the turbulence along the propagation path is required. Correcting for these image aberrations will improve the quality of the target image ...

    STTR Phase I 2018 Department of DefenseAir Force
  10. Complex Object Reflectance Characterization System (CORCS)

    SBC: NUTRONICS, INC.            Topic: AF18AT007

    Nutronics, Inc. and Montana State University propose to develop a method for characterization of the full Mueller matrix for reflective scattering from a test object. The Complex Object Reflectance Characterization System (CORCS) will initially be designed for laboratory use and characterization of test objects by active imaging to measure both the Mueller Matrix and the target depth associated wi ...

    STTR Phase I 2018 Department of DefenseAir Force
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