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. Synthetic Aperture Radar(SAR) Image Generation Data Augmentation

    SBC: ETEGENT TECHNOLOGIES, LTD.            Topic: DTRA21B001

    Machine learning algorithms have demonstrated performance on par with or superior to human analysts on large datasets when sufficient training data is available.  For military applications obtaining sufficient, truthed data is always a challenge.  Three approaches have been used for measured data collections to support sensor exploitation programs: coordinated collections, turntable measurements ...

    STTR Phase II 2023 Department of DefenseDefense Threat Reduction Agency
  2. Phase II: In-field analysis of trace U and Pu by electrochemical pre-concentration

    SBC: AWAREABILITY TECHNOLOGIES, LLC            Topic: DTRA20B003

    The Defense Threat Reduction Agency (DTRA) needs a capability to collect and provide immediate presumptive analysis of radiological/nuclear samples of concern at the source of collection. Such in-field technologies should be capable of detecting and identifying trace quantities of elements and/or chemicals containing plutonium (Pu) and uranium (U), with a focus on chemicals specific to the nuclear ...

    STTR Phase II 2022 Department of DefenseDefense Threat Reduction Agency
  3. Compact Laser Drivers for Photoconductive Semiconductor Switches- STTR Phase II Sequential

    SBC: SCIENTIFIC APPLICATIONS & RESEARCH ASSOCIATES, INC.            Topic: DTRA16A004

    For effective protection against radiated threats, produced by high altitude electromagnetic pulse (HEMP) caused by nuclear detonations and high-power microwave (HPM) Directed Energy (DE) weapons it is important to understand not only the physics of the threats, but also to quantify the effects on mission-critical electrical systems. EMP/HMP simulators enable threat level testing of MCS and provid ...

    STTR Phase II 2022 Department of DefenseDefense Threat Reduction Agency
  4. Hardened, Optically-Based Temperature Characterization of Detonation Environments

    SBC: SA PHOTONICS, LLC            Topic: DTRA19B001

    Improving the effectiveness of counter-WMD operations requires improved understanding of weapon-target interaction. Specifically, time-resolved measurements of temperature and composition are required to allow temporal evolution of a detonation fireball. To address this need, SA Photonics will develop MONITOR, a laser-based temperature diagnostic which will enable wide dynamic range temperature me ...

    STTR Phase II 2022 Department of DefenseDefense Threat Reduction Agency
  5. Computer Vision Image Interpretation for 3D Model Reconstruction

    SBC: TOYON RESEARCH CORPORATION            Topic: DTRA18B001

    Toyon Research Corporation (Toyon) and the University of California, Santa Barbara (UCSB) propose research, development, and demonstration of algorithms and an efficient software prototype for 3D model reconstruction using single images collected via remote sensing. In particular, the effort is focused on processing of high-resolution commercial satellite images for 3D reconstruction of buildings. ...

    STTR Phase II 2021 Department of DefenseDefense Threat Reduction Agency
  6. Numerics-Informed Neural Networks (NINNs)

    SBC: KARAGOZIAN & CASE, INC.            Topic: DTRA21B002

    The overall goal is to develop numerics-informed neural networks (NINNs) and DeepOnets for chemical reactions and for PDEs with spatial derivatives improve the computational efficiency of the chemical kinetics models for chemical weapon agents and simulants. Based on the first NINN developed by the Karniadakis’s group in 2018, which blends the multi-step time-stepping with deep neural networks, ...

    STTR Phase I 2022 Department of DefenseDefense Threat Reduction Agency
  7. Discrete 3-D Electronics for Mobile Radiation Detection Systems

    SBC: RADIATION DETECTION TECHNOLOGIES, INC.            Topic: DTRA18B002

    Phase II will utilize knowledge gained from phase I work to develop and execute a manufacturing process suitable for producing quantities of 3-D printed discrete circuits for radiation detection systems.  The goal is to support mobile radiation detection system requirements for high voltage, analog amplification, and MCA functionality to produce differential pulse height spectra in time sequence. ...

    STTR Phase II 2020 Department of DefenseDefense Threat Reduction Agency
  8. SAR AI Training dataset generated using Reification

    SBC: Arete Associates            Topic: DTRA21B001

    The Synthetic Aperture Radar (SAR) Image Generation Data Augmentation (SIGDA) system is achieved using SAR simulators and the Arete’s Reification approach. Large, realistic datasets will be generated using the Arete Reification capability. These large Reified datasets are then used to train machine learning or Artificial Intelligence (AI), Automatic Target Recognition (ATR) classification algori ...

    STTR Phase I 2022 Department of DefenseDefense Threat Reduction Agency
  9. Obscured Object Training with GAN Augmented Synthetic Data

    SBC: ETEGENT TECHNOLOGIES, LTD.            Topic: DTRA21B001

    Machine learning algorithms have demonstrated performance on par with or superior to human analysts on large datasets when sufficient training data is available. For many military applications, sufficient truthed data over relevant operating conditions does not exist and is prohibitively expensive to obtain. A potential solution to thislack of measured datais synthetic data derived from physics si ...

    STTR Phase I 2022 Department of DefenseDefense Threat Reduction Agency
  10. In-field analysis of trace U and Pu by electrochemical pre-concentration

    SBC: AWAREABILITY TECHNOLOGIES, LLC            Topic: DTRA20B003

    AwareAbility Technologies (AAT), in collaboration with The Ohio State University (OSU), proposes to develop a small hand-held analysis kit for in-field analysis of trace amounts of Uranium (U) and Plutonium (Pu) that will meet or exceed the requirements set by DTRA. Swipe, dust, or water samples would be analyzed by this kit for isotopes and isotopic ratios to indicate the special nuclear material ...

    STTR Phase I 2021 Department of DefenseDefense Threat Reduction Agency
US Flag An Official Website of the United States Government