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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. Adaptive Markov Inference Game Optimization (AMIGO) for Rapid Discovery of Evasive Satellite Behaviors

    SBC: INTELLIGENT FUSION TECHNOLOGY, INC.            Topic: AF17CT02

    Space superiority requires space protection and space situational awareness (SSA), which rely on rapid and accurate space object behavioral and operational intent discovery. The focus of this project is to develop a stochastic approach for rapid discovery of evasive satellite behaviors. Designing the innovative decision support tool has numerous challenges: (i) partial observable actions; (ii) eva ...

    STTR Phase I 2018 Department of DefenseAir Force
  2. Adaptive multi-sensor wide area situational awareness system- MP 85-12

    SBC: METRON INCORPORATED            Topic: AF12BT14

    ABSTRACT: Existing machine learning algorithms have difficulty using all available data about a problem. This STTR will develop a new algorithm that can make full use of all available data, whether that data is labeled or not, and even when some data types or data resolutions are not available during operation. BENEFIT: This STTR will develop a novel machine learning algorithm for reasoning abo ...

    STTR Phase I 2013 Department of DefenseAir Force
  3. Additive Manufacturing Sensor Fusion Technologies for Process Monitoring and Control.

    SBC: X-Wave Innovations, Inc.            Topic: DLA18A001

    Additive Manufacturing (AM) is a modern and increasingly popular manufacturing process for metallic components, but suffers from well known problems of inconsistent quality of the finished product. Process monitoring and feedback control are therefore crucial research areas with a goal of solving this problem. To address this concern, X-wave Innovations, Inc. (XII) and the University of Dayton Res ...

    STTR Phase I 2018 Department of DefenseDefense Logistics Agency
  4. Advanced Mediator Architectures for Efficient Electron Transfer in Enzymatic Fuel Cell Electrodes

    SBC: CFD RESEARCH CORPORATION            Topic: AF09BT03

    Our objective is to develop advanced mediator architectures for efficient electron transfer in enzymatic fuel cells (EFCs) for low power systems. The proposed EFC will leverage ongoing research at both CFDRC and Michigan State University to provide a fully-integrated lightweight, low-cost, manufacturable, and renewable power supply, for various military and civilian applications. EFC systems offer ...

    STTR Phase I 2010 Department of DefenseAir Force
  5. A High Performance and Cost Effective Ultra High Performance Concrete

    SBC: i2C Solutions, LLC            Topic: AF12BT04

    ABSTRACT: Adversarial installations, such as those housing the means for nuclear weapons production, are increasingly being constructed in heavily fortified locations and often using ultra high performance concrete (UHPC) as the construction material. As such, the U.S. Air Force has considerable interest in further developments of ultra high performance concrete (UHPC) to maintain an advantage o ...

    STTR Phase I 2013 Department of DefenseAir Force
  6. 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
  7. A Multi-Modal State and Measurement Filter for RSO Tracking

    SBC: DECISIVE ANALYTICS CORPORATION            Topic: AF09BT11

    Joint Space Operations Center under the United States Strategic Command employs a worldwide network of 29 sensors, known as the Space Surveillance Network (SSN), to track more than 17,000 man-made objects in Earth orbit with sizes 10 centimeters or larger. Decisive Analytics Corporation and the University of Texas Austin Center for Space Research propose an innovate framework for solving stochast ...

    STTR Phase I 2010 Department of DefenseAir Force
  8. Anisotropic Property Manipulation of Selective Laser Melted GRCop-84

    SBC: SPECIAL AEROSPACE SERVICES            Topic: AF18AT009

    In partnership with the Colorado School of Mines Alliance for the Development of Additive Processing Technologies and with support from the Johns Hopkins University Energetic Research Group, Special Aerospace Services will provide the Air Force with characterization of fully dense Selective Laser Melted GRCop-84 subjected to a variety of manipulations that affect key performance metrics for regene ...

    STTR Phase I 2018 Department of DefenseAir Force
  9. Application of Hierarchical Memory Models to Automatic Target Recognition Modeling and Simulation

    SBC: NOVATEUR RESEARCH SOLUTIONS LLC            Topic: AF18AT014

    This SBIR Phase I project proposes a visual processing system for automated target recognition. Inspired by biological vision systems and hierarchical memory models, the proposed system is capable of learning hierarchical invariant features from unlabeled data that are independent of object labels. The model exploits these learned features to create hierarchical representations of target memories ...

    STTR Phase I 2018 Department of DefenseAir Force
  10. Autonomous Decision Making via Hierarchical Brain Emulation-- 19-009

    SBC: METRON INCORPORATED            Topic: AF19AT009

    The objective of this project is to develop human intelligence-inspired algorithms that exploit multi-modal sources of low and high quality data to achieve a series of objectives such as detection, localization, tracking, and classification. A Bayesian model-based hierarchical adaptive decision making (HADM) algorithm will be developed which includes multiple levels of decision making organized in ...

    STTR Phase I 2019 Department of DefenseAir Force
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