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Award Data

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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. Video to Feature Data Association and

    SBC: NOVATEUR RESEARCH SOLUTIONS LLC            Topic: NGA181007

    This SBIR Phase II project proposes a probabilistic approach to determine a vehicle’s location using onboard video and Lidar sensors and foundation map data in GPS denied environments. The proposed system does not rely on only one type of information source, instead it combines proposals from a variety of location estimators to find a vehicles location in GPS-denied environments. The system take ...

    SBIR Phase II 2019 Department of DefenseNational Geospatial-Intelligence Agency
  3. A User-Centric Gamified Crowdsourcing System for Geospatial Analysts

    SBC: 361 INTERACTIVE LLC            Topic: NGA191007

    Creating comprehensive geospatial datasets requires that National Geospatial Agency (NGA) analysts spend large amounts of time searching for, delineating, and labeling non-moving features in overhead imagery. This tiresome and tedious task can negatively impact not only the analysts’ work satisfaction but also the resulting data quality. Fortunately, recent advances in gamification and crowdsour ...

    SBIR Phase I 2019 Department of DefenseNational Geospatial-Intelligence Agency
  4. 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
  5. 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
  6. Automating the Semantic Labeling of Trajectory Data

    SBC: INTELLIGENT MODELS PLUS INC.            Topic: NGA191006

    Advances in location-acquisition and mobile computing techniques have generated massive spatiotemporal trajectory data, which represent the mobility of a diversity of moving objects, such as people, vehicles, and animals. Moreover, recent research has tabbed learning of how to automatically explain and anticipate both the observable and abstract trajectories as one of the likely keys to building t ...

    SBIR Phase I 2019 Department of DefenseNational Geospatial-Intelligence Agency
  7. Asynchronous Active 3D Imaging

    SBC: SCIX3 LLC            Topic: NGA183001

    Recent advances in LiDAR, detector, and airborne systems technology have opened the door to small, high-performance, and significantly lower-cost alternatives over currently deployed airborne LiDAR imaging systems. CSLabs’ proposed initiative leverages modeling and simulation (M&S) to evaluate the efficacy of new approaches with the potential to disrupt the existing LiDAR imaging paradigm. Where ...

    SBIR Phase I 2019 Department of DefenseNational Geospatial-Intelligence Agency
  8. Asynchronous Multi-transmitter Multi-aperture Synthetic 3D Imaging System

    SBC: VOXTEL, INC.            Topic: NGA183001

    Traditional active 3D imaging systems, such as airborne and terrestrial lidar scanners, use a transmitter and receiver typically co-located on the same platform and connected in synchronous communications. However, recent advances in laser, detector, and airborne systems technology have opened the door to smaller, higher-performance and significantly lower-cost airborne lidar systems in which it i ...

    SBIR Phase I 2019 Department of DefenseNational Geospatial-Intelligence Agency
  9. SURFER: SAR Unsupervised and Robust Feature ExtractoR

    SBC: THE DESIGN KNOWLEDGE COMPANY LLC            Topic: NGA191001

    The NGA requires an automatic, unsupervised SAR feature extraction (AUFE) technique, that can ultimately be deployed for geospatial analysis, modeling, and target detection. Our proposed “SAR Unsupervised and Robust Feature ExtractoR” (SURFER) solution includes in Phase I: (1) a sound and deterministic assessment of the underlying RF phenomenology and SAR processing theoretical basis for effec ...

    SBIR Phase I 2019 Department of DefenseNational Geospatial-Intelligence Agency
  10. Improved detection sensitivity, geolocation accuracy, and create novel GEOINT products for OTHR radar systems (IGOR)

    SBC: EXPEDITION TECHNOLOGY, INC.            Topic: NGA191008

    Over the Horizon Radar (OTHR) has been a deployed capability for over 3 decades. OTHR uses the ionosphere to reflect HF radar signals in order to illuminate objects (potential targets) beyond the horizon, giving it a potential effective range of several hundred to a few thousand kilometers. Understanding how the HF radar signals interact and reflect off the ionosphere is crucial to accurate target ...

    SBIR Phase I 2019 Department of DefenseNational Geospatial-Intelligence Agency
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