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The Award database is continually updated throughout the year. As a result, data for FY23 is not expected to be complete until September, 2024.

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. Innovative 2D/3D Building, Asset, and Resource Tracking Visualization Tool

    SBC: KUTTA TECHNOLOGIES, INC.            Topic: N/A

    In this proposal, Kutta capitalizes on existing DOD investments and its own 2D and 3D visualization tools, and leverages the world-renowned computer graphics department at Arizona State University (ASU). This prior work experience and knowledge allows the team to build a resource and asset tracking tool for incident commanders with powerful 2D and 3D visualization capabilities. Kutta and its prest ...

    STTR Phase I 2006 Department of Homeland Security
  2. System for Nighttime and Low-Light Face Recognition

    SBC: POLARIS SENSOR TECHNOLOGIES INC            Topic: SOCOM18A001

    The objective of this proposal is to develop instrumentation and algorithms for acquiring facial features for facial recognition in low- and no-light conditions.We will use cross-spectrum matching by exploiting infrared polarimetric imagery which tends to show features that match more closely visible imagery than conventional infrared.In addition to thermal infrared, we will also test subjects in ...

    STTR Phase I 2018 Department of DefenseSpecial Operations Command
  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. Algorithm Performance Evaluation with Low Sample Size

    SBC: SIGNATURE RESEARCH, INC.            Topic: NGA20C001

    The team of Signature Research, Inc. and Michigan Technological University will develop and demonstrate methods and metrics to evaluate the performance of machine learning-based computer vision algorithms with low numbers of samples of labeled EO imagery. We will use the existing xView panchromatic dataset to demonstrate a proof-of-concept set of tools. If successful, in Phase II, we will extend t ...

    STTR Phase I 2021 Department of DefenseNational Geospatial-Intelligence Agency
  5. sUAS Munition Teaming for Advanced Precision Strike

    SBC: INVARIANT CORPORATION            Topic: SOCOM21C001

    This task seeks to develop advanced teaming via machine learning between small unmanned air systems and Non Line-of-Sight (NLOS) munitions in GPS denied Environments. Current precision targeting capabilities are robust to state errors from ISR targeting platforms and weapons systems seeking to passively acquire a target. Visual Based Navigation (VBN) provides required state information in GPS deni ...

    STTR Phase I 2022 Department of DefenseSpecial Operations Command
  6. Edge Quantum Processor

    SBC: STREAMLINE AUTOMATION LLC            Topic: SOCOM22DST01

    Quantum technology will become a key enabler of future Air Force superiority. Topological insulator (TI) qubits are inherently stable and fault-tolerant because they exploit local topological symmetries and global boundary conditions of chalcogenide materials to yield unique, emergent quantum states. Wake Forest University and Streamline Automation have been working collaboratively for the last se ...

    STTR Phase I 2022 Department of DefenseSpecial Operations Command
  7. SeaCraft / AeroNautical Data-collector (SCAND) for real-time target recognition

    SBC: HYDRONALIX INC            Topic: SOCOM22DST01

    Intelligent detection and imaging technology hold considerable value for Department of Defense to attain situational awareness and advantage over opposing forces, and for aid in navigating potentially dangerous marine and terrestrial environments. Technologies obtain intelligence on underwater threats and can gather intelligence on approaching surface threats. Current sensor technologies require a ...

    STTR Phase I 2022 Department of DefenseSpecial Operations Command
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