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The Award database is continually updated throughout the year. As a result, data for FY20 is not expected to be complete until September, 2021.

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.

  1. Long-term Patterns of Life from Sporadic Observations

    SBC: Novateur Research Solutions, LLC            Topic: NGA192005

    This SBIR Phase-I project will develop novel approaches for unsupervised life-long learning architecture to extract long-term patterns of life from sporadic observations. The proposed architecture models longterm dependencies, learns associations between features from sensory observations and the contexts in which these features occur, identifies sudden changes in the patterns for anomaly detecti ...

    SBIR Phase I 2020 Department of DefenseNational Geospatial-Intelligence Agency
  2. GLANCE: Graph Learned Anomalies in Changing Environments

    SBC: Expedition Technology, Inc.            Topic: NGA192005

    While Wide Area Motion Imagery (WAMI) activity analysis has considerably advanced for continuous tracking—particular through adoption of improved machine learning (ML) methods, less research has been applied to using similar quality image sequences over sporadic intervals to characterize site activity. While pure still-image remote sensing collection can characterize basic change detection usin ...

    SBIR Phase I 2020 Department of DefenseNational Geospatial-Intelligence Agency
  3. Learning traffic camera locations using vehicle re-identification

    SBC: Arete Associates            Topic: NGA201005

    In its effort to provide necessary intelligence and analysis, the National Geospatial-Intelligence Agency (NGA) utilizes extensive traffic camera systems. However, the large amount of data overwhelms both analysts and existing processing methods. In order to provide a better understanding and reduce the search space for common problems such as target tracking, it is necessary to extract the camera ...

    SBIR Phase I 2020 Department of DefenseNational Geospatial-Intelligence Agency
  4. Bounding generalization risk for Deep Neural Networks

    SBC: Euler Scientific            Topic: NGA20A001

    Deep Neural Networks have become ubiquitous in the modern analysis of voluminous datasets with geometric symmetries. In the field of Particle Physics, experiments such as DUNE require the detection of particle signatures interacting within the detector, with analyses of over a billion 3D event images per channel each year; with typical setups containing over 150,000 different channels.  In an ...

    STTR Phase I 2020 Department of DefenseNational Geospatial-Intelligence Agency
  5. Faster Optical Modem for Underwater Data Acquisition

    SBC: SA Photonics, Inc.            Topic: NGA182001

    SA Photonics’ Optical Navigation and Ranging (ONAR) system is an interrogative system that operate underwater in wavelength range of blue/green (450-540 nm) and enables navigational correction to IMU based dead reckoning navigation. The location based beacons are battery operated and have operational life span of over one year. The system is designed to operate in on demand burst mode so that no ...

    SBIR Phase I 2019 Department of DefenseNational Geospatial-Intelligence Agency
  6. Faster Optical Modem for Underwater Data Acquisition

    SBC: Sonalysts, Inc.            Topic: NGA182001

    To address NGA’s requirements, Sonalysts’ team of world-class experts in underwater optical communication proposes development and implementation of the Precision Optical Navigation Transceiver for Undersea Systems (PONTUS). PONTUS will transfer navigation information from an Underwater Navigation Beacon (UNB) to an Unmanned Undersea Vehicle (UUV) in an electromagnetic-spectrum-denied (e.g., G ...

    SBIR Phase I 2019 Department of DefenseNational Geospatial-Intelligence Agency
  7. A Multi-Branch Network for Automated VNIIRS Assessment of Motion Imagery

    SBC: TOYON RESEARCH CORPORATION            Topic: NGA191003

    Due to the lack of consistency in existing automated methods for assigning VNIIRS levels to motion imagery, and the overwhelming human resources required to manually assign levels, a new method of automated/semi-automated VNIIRS assessment is needed. In recent years, advancements in deep learning have provided solutions to previously intractable computer vision problems. In many cases, automated d ...

    SBIR Phase I 2019 Department of DefenseNational Geospatial-Intelligence Agency
  8. 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
  9. 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
  10. Multi-hop processing for OTHR range extension (MOHAIR)

    SBC: Expedition Technology, Inc.            Topic: NGA191011

    Over the Horizon Radar (OTHR) has been a deployed capability for over 3 decades and 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 thousand kilometers. This range is impressive, but it assumes/takes advantage of only one bounce off of the ionosphere. The capability to take advan ...

    SBIR Phase I 2019 Department of DefenseNational Geospatial-Intelligence Agency
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