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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. 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
  2. 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
  3. 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
  4. Improved Image Processing for Low Resolution Imagery with Inter-Frame Pose Variation

    SBC: ETEGENT TECHNOLOGIES, LTD.            Topic: NGA172009

    With respect to digital imaging sensors and systems, obtaining as many pixels on target is a necessity to classify or identify a target for real-time operations and forensic analysis within the intelligence community. Rather than relying on improved sensors, the approach originally solicited and further refined here utilizes super-resolution image processing techniques to provide more detail in th ...

    SBIR Phase II 2019 Department of DefenseNational Geospatial-Intelligence Agency
  5. Advanced Image Segmentation for Radar Imagery

    SBC: ELECTROMAGNETIC SYSTEMS, INC.            Topic: NGA172004

    Implement methods to improve our Phase I architecture for complex SAR imagery collected from different systems and with different collection parameters. Implement techniques to boost performance across all ground features of interest. Reduce the amount of human intervention needed for training our SAR image segmentation architecture.  SAR segmentation can be applied to a number of areas: Intellig ...

    SBIR Phase II 2019 Department of DefenseNational Geospatial-Intelligence Agency
  6. Low-Shot Detection in Remote Sensing Imagery

    SBC: TOYON RESEARCH CORPORATION            Topic: NGA172002

    Toyon Research Corporation proposes to develop algorithms that improve the precision and recall of neural networks for low-shot object classification and detection. Our approach is based upon developing a descriptive multi-domain feature representation of the low-shot target as well as the surrounding context. A multi-branch neural network merges the various domains of information to perform accur ...

    SBIR Phase II 2019 Department of DefenseNational Geospatial-Intelligence Agency
  7. 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
  8. Generalized Change Detection to Cue Regions of Interest

    SBC: TOYON RESEARCH CORPORATION            Topic: NGA181006

    Toyon proposes to research and develop algorithms for generalized salient change detection, and to incorporate these algorithms into software tools implemented on the cloud. Our approach leverages the two most promising methods from Phase I, both based on supervised learning. The first method is the entropy-based feature vector and corresponding neural network, which we will apply at a coarse sear ...

    SBIR Phase II 2019 Department of DefenseNational Geospatial-Intelligence Agency
  9. Hybrid DNN-based Transfer Learning and CNN-based Supervised Learning for Object Recognition in Multi-modal Infrared Imagery

    SBC: TOYON RESEARCH CORPORATION            Topic: 1

    On this effort Toyon Research Corp. and The Pennsylvania State University are developing deep learning-based algorithms for object recognition and new class discovery in look-down infrared (IR) imagery. Our approach involves the development of a hybrid classifier that exploits both transfer learning and semi-supervised paradigms in order to maintain good generalization accuracy, especially when li ...

    STTR Phase I 2018 Department of DefenseNational Geospatial-Intelligence Agency
  10. 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
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