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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. OPTICAL SHUTTER FOR ACTIVE RANGE-GATED ELECTRO-OPTIC IMAGING

    SBC: TP ENGINEERING SERVICES, LLC            Topic: NGA212001

    TP Engineering personnel have extensive experience with electro-optic systems and high Pulse Repetition Frequency (PRF) Laser systems. We have detailed knowledge of Pockels cell systems enabling active gated imaging through foliage at PRF 100 kHz PRF. Such systems can dramatically improve and protect Geiger-mode LIDAR by both controlling the transmitter output and gating out unwanted return lig ...

    SBIR Phase I 2022 Department of DefenseNational Geospatial-Intelligence Agency
  2. Dynamic Parameter Selection for Community Detection Algorithms (Graph Networks)

    SBC: Arete Associates            Topic: NGA212002

    In the pattern of life problem space, data is often represented via mathematical graphs, in which a variety of algorithms may be employed to conduct semi-autonomous analysis. While successful empirical application of graph-domain algorithms on ABI problems has been achieved, most of these algorithms require a tuning parameter, which is often set heuristically in real-world scenarios. Arete has dev ...

    SBIR Phase I 2022 Department of DefenseNational Geospatial-Intelligence Agency
  3. Structured Stories for MOVINT

    SBC: Arete Associates            Topic: NGA203001

    Arete will integrate the Mover Intelligence Extraction Engine with the Social Structured Framework (SSF) to produce a capability to generate narratives of MOVINT track data with context derived from associated Geographic Information Systems (GIS) and other foundation data. The Extraction Engine will be derived from the Arete Cognitive Behavior Classifier (CBC) to characterize MOVINT tracks into co ...

    SBIR Phase I 2021 Department of DefenseNational Geospatial-Intelligence Agency
  4. Algorithm Performance Evaluation with Low Sample Size

    SBC: SIGNATURE RESEARCH, INC.            Topic: NGA20C001

    The team of Signature Research, Inc. and Michigan Technological University will develop and demonstrate methods and metrics to evaluate the performance of machine learning-based computer vision algorithms with low numbers of samples of labeled EO imagery. We will use the existing xView panchromatic dataset to demonstrate a proof-of-concept set of tools. If successful, in Phase II, we will extend t ...

    STTR Phase I 2021 Department of DefenseNational Geospatial-Intelligence Agency
  5. A Multiphysics Approach to Radio Frequency Modeling of Ablators in Ionized Hypersonic Flow

    SBC: ATA ENGINEERING, INC.            Topic: NGA203002

    ATA Engineering, Inc., (ATA) proposes to develop and demonstrate a multiphysics framework for the radar cross-section (RCS) analysis of an ablating hypersonic vehicle in an ionized plasma flow field. ATA has developed a software toolset, known as the Multiphysics Engine, capable of modeling many of these hypersonic phenomena. It couples state-of-the-art solvers for CFD (Loci/CHEM), ablation (CHAR) ...

    SBIR Phase I 2021 Department of DefenseNational Geospatial-Intelligence Agency
  6. Topological Data Analysis for Automated Annotation of EO/SAR Datasets

    SBC: Arete Associates            Topic: NGA203005

    In recent years, it has become increasingly important to conduct Geospatial Intelligence (GEOINT) operation via commercial and government persistent sensor systems, which have produced a copious amount of data relevant to the National Geospatial-Intelligence Agency (NGA). As the supply of data expands, it is necessary to employ automated analytics to exploit the data efficiently. We cannot rely on ...

    SBIR Phase I 2021 Department of DefenseNational Geospatial-Intelligence Agency
  7. Graphical Methods for Discovering Structure and Context in Large Datasets

    SBC: MAYACHITRA, INC.            Topic: NGA203005

    The ubiquity of image sensors for data collection creates a glut of data, which leads to bottlenecks in the processing capabilities of modern systems. In order to process this data, meticulously labeled datasets are required and that must be reviewed by humans in order to guarantee state-of-the-art performance. In this effort we endeavor to create a system that can automatically exploit salient in ...

    SBIR Phase I 2022 Department of DefenseNational Geospatial-Intelligence Agency
  8. Automated Camera Orientation Recovery Software

    SBC: Physical Optics Corporation            Topic: NGA201006

    To address the NGA’s need to fully automate recovery of camera orientation parameters from ground-level imagery, Physical Optics Corporation (POC) proposes to develop new Automated Camera Orientation Recovery Software (ACORS). It is based on a new, multicue combination of algorithms for finding true horizon lines in images. Specifically, the innovation in locating occluded true horizon lines bel ...

    SBIR Phase I 2021 Department of DefenseNational Geospatial-Intelligence Agency
  9. 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
  10. 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
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