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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. 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
  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. Self-Supervised Training in Geospatial Applications with a Robust Hierarchical Vision Transformer (STAR)

    SBC: UNIVERSITY TECHNICAL SERVICES, INC.            Topic: OSD22A001

    Satellite Imagery in Geospatial Intelligence (GEOINT), in conjunction with imagery intelligence (IMINT), geospatial information, and other means of gaining intelligence, has greatly improved the potential of the warfighter and decision makers enabling them to gain a more comprehensive perspective, an in-depth understanding, and a cross-functional awareness of the operational environment. The Artif ...

    STTR Phase I 2022 Department of DefenseNational Geospatial-Intelligence Agency
  4. 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
  5. 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
  6. 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
  7. 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
  8. 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
  9. 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
  10. KAIZEN: Knowledge Aware Intelligent Zero-shot Explainable Multi-Modal Network

    SBC: Intelligent Automation, Inc.            Topic: NGA203005

    Detecting relevant objects of interest in large datasets using artificial intelligence techniques is very appealing. However, most state of the art approaches use deep neural network techniques -- requiring millions of human annotated training examples. These datasets mostly come from academia and don’t transfer well to novel domains. Even with the use of smaller annotated datasets and an applic ...

    SBIR Phase I 2021 Department of DefenseNational Geospatial-Intelligence Agency
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