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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. CHATMAN Phase II

    SBC: Stratagem Group, Inc., The            Topic: OSD221001

    Reducing the False Alarm Rate (FAR) of Automated Target Recognition (ATR) algorithms for Synthetic Aperture Radar (SAR) imagery is crucial for Intelligence, Surveillance, Reconnaissance (ISR) and precision target engagement missions. While modern Deep Learning (DL) ATR networks have demonstrated advanced predictive capabilities and generalization for SAR imagery, they lack spatial awareness, resul ...

    SBIR Phase II 2023 Department of DefenseNational Geospatial-Intelligence Agency
  2. Scene Geometry Aided Automatic Target Recognition (ATR) for Radar

    SBC: Stratagem Group, Inc., The            Topic: OSD221001

    Reducing the false alarm rate (FAR) of Automated Target Recognition (ATR) algorithms is crucial for intelligence, surveillance, reconnaissance (ISR) and precision target engagement missions. There are many contributing factors that result in higher FAR for deep learning (DL) ATR networks operating on Synthetic Aperture Radar (SAR) imagery, including: image distortions, unrepresentative target sign ...

    SBIR Phase I 2022 Department of DefenseNational Geospatial-Intelligence Agency
  3. Auto-Label SAR (AL-SAR)

    SBC: ICR, INC.            Topic: OSD221002

    Correctly labeled data is essential for training AI/ML-based automatic target recognition (ATR). The training process is all the more complicated in synthetic aperture radar (SAR) images because of their unique phenomenology, such as orientation-sensitive target signatures, layover, cross-range smearing, and radio frequency interference. New automated technology must reduce the cost and acc ...

    SBIR Phase I 2022 Department of DefenseNational Geospatial-Intelligence Agency
  4. CREATIVE PERCEPTION: Grey Matters’ Semi-supervised detection remote sensing prototype algorithm suite

    SBC: GREY MATTERS DEFENSE SOLUTIONS, LLC            Topic: NGA201003

    The National Geospatial Intelligence Agency (NGA) requires a state-of-the-art model to quickly find and define new target sets within ever increasing datasets. Grey Matters’ CREATIVE PERCEPTION will provide the NGA with an advanced detection algorithm suite that can be easily upgraded to new target sets with a minimum amount of labeled training data. CREATIVE PERCEPTION, based on a complex sel ...

    SBIR Phase I 2021 Department of DefenseNational Geospatial-Intelligence Agency
  5. Knowledge Graph-Based Collaborative Recommender System (KCRS) for Spatio-Temporal Intelligence Documents

    SBC: NUMERICA CORPORATION            Topic: NGA191005

    US military and intelligence agencies, including the NGA, 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. NGA analysts are often overwhelmed with data and spend too much time solving data problems rather than solving intelligence problems. Thus, there ...

    SBIR Phase II 2021 Department of DefenseNational Geospatial-Intelligence Agency
  6. 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
  7. 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
  8. High-Sensitivity Military GPS Receivers

    SBC: THE NAVSYS CORPORATION            Topic: NGA07001

    Many military users need to operate in areas where GPS signal reception is impeded by building walls, dense foliage and urban canyon. Current military GPS receivers do not operate robustly in these environments which include multipath and varying signal levels caused by partial blockage/non-penetration of signals through different materials. Some vendors in the commercial sector, however, have b ...

    SBIR Phase I 2008 Department of DefenseNational Geospatial-Intelligence Agency
  9. SAR Tomography

    SBC: VEXCEL CORP.            Topic: NIMA03002

    The development of tomographic SAR imaging is arguably the next big step in the evolution of imaging radar systems. The value of a successful volumetric imaging system to the US Government is clear. While successful demonstrations of volumetric imaging capabilities from various radar platforms have been made recently, there remains significant issues regarding data acquisition, signal processing ...

    SBIR Phase II 2004 Department of DefenseNational Geospatial-Intelligence Agency
  10. SAR Tomography

    SBC: VEXCEL CORP.            Topic: N/A

    The primary goal of the proposed research is to help advance the science and art of SAR tomography and, more generally, 3-D SAR imaging for downstream image exploitation. Vexcel Corporation proposes to delineate the current state-of-the-art in SARtomography for 3-D imaging and subsequent exploitation. There have been a number of tomographic SAR examples described in the literature and elsewhere, h ...

    SBIR Phase I 2003 Department of DefenseNational Geospatial-Intelligence Agency
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