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The Award database is continually updated throughout the year. As a result, data for FY20 is not expected to be complete until September, 2021.

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.

  1. Active Imaging through Fog

    SBC: SA Photonics, Inc.            Topic: N18AT021

    Active imaging systems are used to for imaging in degraded visual environments like that found in marine fog and other environments with a high level of attenuation and scattering from obscurants like fog, rain, smoke, and dust.These systems are still limited in range and resolution. SA Photonics is taking advantage of multiple image enhancement techniques, like wavelength tunability, pulse contro ...

    STTR Phase I 2018 Department of DefenseNavy
  2. Adaptive Fleet Synthetic Scenario Research

    SBC: KAB LABORATORIES INC.            Topic: N10AT044

    Synthetic scenario-based training of Navy personnel in the use of Navy SIGINT/IO systems has helped to reduce training costs, and it has enabled the personnel to be trained in an environment that sufficiently approximates real-world situations that could not otherwise be accomplished within the class room. However, scenario development is highly complex and involves a great deal of human effo ...

    STTR Phase I 2010 Department of DefenseNavy
  3. Adaptive Learning for Stall Pre-cursor Identification and General Impending Failure Prediction

    SBC: Frontier Technology Inc.            Topic: N10AT008

    Frontier Technology, Inc. (FTI) and Northeastern University propose to investigate and develop an innovative approach to predict stall events of aircraft engines prior to occurrence and in sufficient time to allow the FADEC controller to adjust engine variables. The team will utilize vector quantization and neural network techniques to develop accurate models of engine behavior that will be used t ...

    STTR Phase I 2010 Department of DefenseNavy
  4. Additive Manufacturing of Metallic Materials for High Strain Rate Applications

    SBC: MRL MATERIALS RESOURCES LLC            Topic: MDA17T001

    Metallic additive manufacturing (AM) is an attractive technology for the production of lethality test articles due to the potential for significantly reduced lead time and manufacturing cost.However, in order to be effective in providing accurate lethality data, the properties of the AM material have to match closely the properties of conventionally manufactured alloys found in real threat targets ...

    STTR Phase I 2018 Department of DefenseMissile Defense Agency
  5. Additive Manufacturing of Multifunctional Nanocomposites

    SBC: Sciperio, Inc.            Topic: A13AT010

    Sciperio with team members Georgia Institute of Technology and Centecorp have teamed up to develop an Additive Manufacturing Composite using nano and micro fillers. The team will develop multi-scale models that are supported by experimental characterization for advanced 3D Printable materials. Inelastic response of high strength hierarchical structures composed of engineered materials and specif ...

    STTR Phase I 2013 Department of DefenseArmy
  6. Additive Manufacturing Sensor Fusion Technologies for Process Monitoring and Control.

    SBC: ARCTOS Technology Solutions, LLC            Topic: DLA18A001

    Universal Technology Corporation (UTC) has teamed with the University of Dayton Research Institute (UDRI), Stratonics, and Macy Consulting to demonstrate not only the transitionability into commercial systems, but also to develop the data analytics and monitoring and control requirements to extract the full value fromseveral sensors, including the Stratonics ThermaViz, acoustic and profilometry se ...

    STTR Phase I 2018 Department of DefenseDefense Logistics Agency
  7. Advanced Command and Control Architectures for Autonomous Sensing

    SBC: TOYON RESEARCH CORPORATION            Topic: N18BT030

    We propose to develop an innovative open architecture for the semi-autonomous command and control (C2) of teaming Unmanned Aircraft Systems (UAS). The proposed architecture, based upon Toyon’s Decentralized Asset Management system, supports both centralized and decentralized fusion and control autonomy solutions as well as hybrids approaches. Leveraging STANAG-4586, TCP/IP, UPD, Google™ protob ...

    STTR Phase I 2019 Department of DefenseNavy
  8. Advanced Computational Methods for Study of Electromagnetic Compatibility

    SBC: Hypercomp, Inc.            Topic: AF09BT13

    The leakage of electromagnetic (EM) energy into air vehicles, and particularly into ordnance, poses a hazard that requires careful evaluation. Under current guidelines, such evaluations are primarily to be carried out through extensive testing of items under possible field conditions, a process that can be both time-consuming and costly. The scope of this STTR Phase I activity is to implement a h ...

    STTR Phase I 2010 Department of DefenseAir Force
  9. Advanced Computational Methods for Study of Electromagnetic Compatibility

    SBC: MATHEMATICAL SYSTEMS & SOLUTIONS, INC.            Topic: AF09BT13

    The present text proposes development of efficient, accurate and rapidly-convergent algorithms for the simulation of propagation and scattering of electromagnetic fields within and around structures that (i) Consist of complex combinations of penetrable materials as well as perfect and imperfect conductors, and, (ii) Possess complex geometrical characteristics, including open surfaces, metallic c ...

    STTR Phase I 2010 Department of DefenseAir Force
  10. Advanced Data Processing, Storage and Visualization Algorithms for Structural Health Monitoring Sensor Networks of Naval Assets

    SBC: ACELLENT TECHNOLOGIES, INC            Topic: N10AT042

    Acellent Technologies Inc. and Prof. F. G. Yuan at North Carolina State University (NCSU) are proposing to develop a Hybrid Distributed Sensor Network Integrated with Self-learning Symbiotic Diagnostic Algorithms and Models to determine materials state awareness and its evolution, including identification of precursors, detection of microdamages and flaws near high stress area or in a distributed ...

    STTR Phase I 2010 Department of DefenseNavy
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