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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. Automating Procedural Modeling of Buildings from Point Cloud Data

    SBC: DIGNITAS TECHNOLOGIES, LLC            Topic: NGA183002

    Newer techniques in data collection such as Lidar and photogrammetry can provide large quantities of accurate and up-to-date source data models in operational areas, but transforming this often massive amount of raw source data into a lightweight 3D representation that can be quickly consumed by defense customers using a web browser or mobile devices remains a challenging problem. While point clou ...

    SBIR Phase I 2019 Department of DefenseNational Geospatial-Intelligence Agency
  2. Boost- A System to Suppress False Alarms from Automated Target Recognizers

    SBC: SEED INNOVATIONS, LLC            Topic: NGA181003

    Seed Innovations and subcontractor BIT Systems, a division of CACI International, apply our experience in machine learning, data analytics andimage processing to accomplish the research for the SBIR topic: Suppression of false alarms in Automated Target Recognizers (ATR) that useMachine Learning. With the amount of available imagery data increasing and adversaries vehicles and tactics becoming mor ...

    SBIR Phase I 2018 Department of DefenseNational Geospatial-Intelligence Agency
  3. Source Approval for B-52 Wing to Fairing Seal

    SBC: MAINSTREAM ENGINEERING CORP            Topic: DLA181007

    Increased competition and improved lead times are desired by the Defense Logistics Agency (DLA) for a number of NESO items with annual demand values over $10,000 and fewer than two approved sources. Mainstream Engineerings unique integration of engineering, manufacturing, quality control, and integrated logistics support (ILS) provides the government with the best value for the proposed NSN.The B- ...

    SBIR Phase I 2018 Department of DefenseDefense Logistics Agency
  4. Additive Manufacturing Sensor Fusion Technologies for Process Monitoring and Control.

    SBC: SENVOL LLC            Topic: DLA18A001

    The Department of Defense (DoD) has a demand for out-of-production parts to maintain mission readiness of various weapons platforms. Additive manufacturing (AM) is an exciting and promising manufacturing technique that can make out-of-production parts and holds the potential to solve supply chain issues, such as high costs (i.e. for low-volume parts) and sole sourcing risks. The ability of AM to s ...

    STTR Phase I 2018 Department of DefenseDefense Logistics Agency
  5. Multi-hop processing for OTHR range extension

    SBC: DECIBEL RESEARCH, INC.            Topic: NGA191011

    The development of sophisticated anti-access/area denial (A2/AD) capabilities by our adversaries requires us to develop long range capabilities to mitigate this A2/AD threat. Extending the range of Over The Horizon Radars beyond their conventional single hop operating mode will potentially provide coverage out to 10000 km and beyond. We propose combining existing state-of-the art HF radar ray prop ...

    SBIR Phase I 2019 Department of DefenseNational Geospatial-Intelligence Agency
  6. Reverse Engineering of MILSTAR Battery Pack

    SBC: MAINSTREAM ENGINEERING CORP            Topic: DLA182003

    Increased competition and improved lead times are desired by the Defense Logistics Agency (DLA) for the MILSTAR system battery assembly. Mainstream Engineerings unique integration of engineering, manufacturing, quality control, and integrated logistics support (ILS) provides the government with the best value for the proposed NSN.The MILSTAR nickel-metal hydride battery pack lacks sufficient comme ...

    SBIR Phase I 2018 Department of DefenseDefense Logistics Agency
  7. Danesfield Courier: Efficient Transmission and Rendering of CORE3D Models

    SBC: KITWARE INC            Topic: NGA183002

    An important application for geospatial 3D models is fast transmission and rendering for disadvantaged users who have only a web browser and a limited bandwidth connection. Point cloud models commonly used within the NGA are too large for efficient transmission and rendering. Kitware’s new research on the IARPA CORE3D program has demonstrated procedural building models from point clouds for more ...

    SBIR Phase I 2019 Department of DefenseNational Geospatial-Intelligence Agency
  8. Laser-Aided Automated Removal of Anti-Reflective Coatings From Germanium Substrates

    SBC: ADA TECHNOLOGIES, INC.            Topic: DLA183015

    High-purity germanium (Ge) is manufactured into infrared (IR) lenses for most DoD night sight IR optics, thermal imaging systems, and IR tracking systems in combat vehicles. A recent report by Umicore (ADA’s partner for this proposed project) identifies several current and future needs for Ge, showing growing needs in the middle of severe shortfall. These applications are essential for tracking ...

    SBIR Phase I 2019 Department of DefenseDefense Logistics Agency
  9. Collaborative Recommender System for Spatio-Temporal Intelligence Documents

    SBC: NUMERICA CORPORATION            Topic: NGA191005

    US military and intelligence agencies have invested significant resources in data collection and effective search and analytics tools. However, due to increasing amounts of data, finding relevant information has become more difficult. Thus, there is an important need for recommender system technology that pushes relevant un-queried data to analysts through automation and machine learning technique ...

    SBIR Phase I 2019 Department of DefenseNational Geospatial-Intelligence Agency
  10. Collaborative Recommender System for Spatio-Temporal Intelligence Documents

    SBC: RAJI BASKARAN LLC            Topic: NGA191005

    NLP pipelines available today are getting robust for general language modeling purposes. But domain-specific data, abbreviations and lingos, and text about time or space still need a lot of tuning and training that are well beyond application of standard tool sets. Deep learning for recommendation engines is quite new, and all recommender systems, in particular for specially trained users, tend to ...

    SBIR Phase I 2019 Department of DefenseNational Geospatial-Intelligence Agency
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