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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. Generative Modeling of Multispectral Satellite Imagery

    SBC: NOVATEUR RESEARCH SOLUTIONS LLC            Topic: DTRA22D001

    This STTR Phase I project proposes novel deep learning models for generating realistic multi-spectral remote sensing imagery, specifically in the infrared (IR) and near-infrared (NIR) bands. The proposed system enables synthesis of semantically realistic imagery and provides parametric control of synthesizing objects-of-interest, type of terrain and land cover, time or season, weather, cloud cover ...

    STTR Phase I 2023 Department of DefenseDefense Threat Reduction Agency
  2. Generative Modeling of Multispectral Satellite Imagery

    SBC: Applied Research In Acoustics LLC            Topic: DTRA22D001

    To address the challenge DTRA faces in identifying rare objects of interest to defeat improvised threat networks using multispectral imagery, small business ARiA and research institution Michigan Technological University (MTU) will develop and demonstrate the feasibility of the Generative Augmentation Process (GAP). The Phase I effort will (1) conduct a proof-of-concept study for GAP by developing ...

    STTR Phase I 2023 Department of DefenseDefense Threat Reduction Agency
  3. Environmentally Friendly UAV Coatings for Thermal and IR Management

    SBC: LUNA LABS USA LLC            Topic: A21CT026

    Advancements in thermal/infrared imaging can potentially permit improved detection of assets critical to the U.S. Warfighter, potentially affecting mission outcome. In other situations, improved heat trapping/thermal management may also be beneficial, especially in cold environments. To meet thermal management needs like these, Luna Labs proposes to develop a high-performing but more occupational ...

    STTR Phase II 2023 Department of DefenseArmy
  4. High Volume Extinction Metal Fibers as Next-Generation Artillery Obscurants

    SBC: LUNA LABS USA LLC            Topic: A21CT019

    Military obscurants effectively absorb, scatter, or emit radiation in the visible, infrared and millimeter wavelength ranges to disrupt the line of sight between the target and observer. These aerosolized materials play a crucial role in preventing the detection of the US Warfighter by enemy sensors including seekers, trackers, optical devices, and the human eye. Recently, the Army has expressed i ...

    STTR Phase II 2023 Department of DefenseArmy
  5. High Volume Extinction Metal Fibers as Next-Generation Artillery Obscurants

    SBC: LUNA LABS USA LLC            Topic: A21CT019

    Military obscurants effectively absorb, scatter, or emit radiation in the visible, infrared and millimeter wavelength ranges to disrupt the line of sight between the target and observer. These aerosolized materials play a crucial role in preventing the detection of the US Warfighter by enemy sensors including seekers, trackers, optical devices, and the human eye. Recently, the Army has expressed i ...

    STTR Phase I 2022 Department of DefenseArmy
  6. Environmentally Friendly UAV Coatings for Thermal and IR Signature Management

    SBC: LUNA LABS USA LLC            Topic: A21CT026

    Modern infrared imagers can potentially detect the thermal signature of small unmanned aerial vehicles (UAV)s used by the U.S. Warfighter, potentially affecting mission outcome. To overcome this, Luna proposes to develop a novel, environmental safety and occupational health (ESOH)-friendly coating for thermal and infrared control. The coating will consist of Luna’s propriety resin chemistry and ...

    STTR Phase I 2022 Department of DefenseArmy
  7. Verification, Validation, Assurance, and Trust of Machine Learning Models and Data for Safety-Critical Applications in Armaments Systems

    SBC: Applied Research In Acoustics LLC            Topic: A22BT002

    To address the challenges posed by verification and validation (V&V) of artificial-intelligence (AI) and machine-learning (ML) for high assurance in safety-critical functions of armaments systems, ARiA and Arizona State University (ASU) will develop and demonstrate the feasibility of the Machine Learning Qualification Process (MLQP). The Phase I effort will (1) research and develop fundamental met ...

    STTR Phase I 2022 Department of DefenseArmy
  8. Multi-Phase Blast Munitions via RM/HE Synergy

    SBC: MATSYS INCORPORATED            Topic: A22BT004

    The next generation of Army munitions is aligned with DoD priorities and aims at increasing overmatch capabilities by extending range, including guidance systems while increasing lethality via blast effects. These objectives are typically not compatible in systems sharing a fixed volume and weight. Many munition systems have received propulsion and guidance upgrades over the years; however, most o ...

    STTR Phase I 2022 Department of DefenseArmy
  9. Agile Machine Learning in Dynamic Environments for Complex Event Processing

    SBC: NOVATEUR RESEARCH SOLUTIONS LLC            Topic: A22BT010

    Under this STTR Phase I project, we propose a framework for complex event detection that addresses the limitations of the state-of-the-art by effectively combining deep learning models with neuro-symbolic reasoning. In our approach, we apply a joint deep neural network (DNN) and statistical relational learning (SRL) based framework that combines semantic reasoning and relational learning with data ...

    STTR Phase I 2022 Department of DefenseArmy
  10. Synthetic Platform for Device-Agnostic Quantum Dot IR Photodectors

    SBC: TETRAMER TECHNOLOGIES LLC            Topic: A22BT019

    The objective of this Phase I STTR is to identify materials and methods for the development of a highly robust, predictive synthetic model that will be used to manufacture on-demand Colloidal Quantum Dot (CQD) as absorbers for infrared (IR) photodetectors. The goal for the STTR program is to identify materials that will enable uncooled or thermoelectrically cooled, small and low-weight IR sensors ...

    STTR Phase I 2022 Department of DefenseArmy
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