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Award Data

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The Award database is continually updated throughout the year. As a result, data for FY23 is not expected to be complete until September, 2024.

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. Visual Tools and Progressive Automation for Complex Knowledge Management and Decision Support

    SBC: Stottler Henke Associates, Inc.            Topic: N17AT004

    We propose to adapt and automate the processes and technologies associated with evidence-based decision support to the Navy—providing a tool that can synthesize current cognitive and learning science knowledge and inform decisions so as to maximize the value gained for each training expenditure. We will develop a plug-play architecture that will allow us to make the best use of emerging technolo ...

    STTR Phase II 2019 Department of DefenseNavy
  2. High Density Capacitors for Compact Transmit and Receive Modules

    SBC: Bioenno Tech, LLC            Topic: N17AT011

    Development of high-energy-density, low-loss capacitors for power conversion/conditioning systems is an enabling technology to achieve the objective of reducing size, weight, and cost of transmit and receive (T/R) modules in modern radar and electronic warfare transmitters. Among capacitor technologies available, multilayer ceramic capacitors (MLCCs) are receiving more attentions. At present, howe ...

    STTR Phase II 2019 Department of DefenseNavy
  3. Protocol Feature Identification and Removal

    SBC: P & J ROBINSON CORP            Topic: N18AT018

    Protocols used for communication suffer bloat from a variety of sources, such as support for legacy features or rarely used (and unnecessary) functionality. Traditionally, the Navy subscribes to a blanket adoption of a standard protocol "as is". Unnecessary features are active and can be accessed by both internal and external systems creating security vulnerabilities. PJR Corporation's (PJR's) Pha ...

    STTR Phase II 2019 Department of DefenseNavy
  4. ARCHIMEDES

    SBC: SOAR TECHNOLOGY INC            Topic: N17AT004

    Evidence-based guidelines derived from the learning sciences literature can be applied to training-requirements decisions. However, accessing the state-of-the-art in the learning sciences and applying its lessons to specific training design and analysis questions can be difficult, especially for those not already familiar with the learning sciences. ARCHIMEDES, the software tool proposed in this e ...

    STTR Phase II 2019 Department of DefenseNavy
  5. Soliloquy Ph II

    SBC: SOAR TECHNOLOGY INC            Topic: N17AT010

    Automatic Speech Recognition (ASR) allows trainees to practice verbal communication skills in representative training environments without the need for human role players. However, these technologies have yet to become a feature of most training systems. Building on Phase I work, SoarTech along with our academic partners at UC Davis, proposes developing Soliloquy, a novel interface that allows non ...

    STTR Phase II 2019 Department of DefenseNavy
  6. Full Featured Low-Cost HMS for Combatant Craft

    SBC: QUALTECH SYSTEMS INC            Topic: N18AT015

    Qualtech Systems, Inc. (QSI), in collaboration with Vanderbilt University (VU) proposes to develop a state-of-the art Health Management System (HMS) system consisting of a small form factor GPS-enabled onboard computer, a small display for crew, and sensors for boat and engine vibration, OBD data, engine oil quality monitoring, and battery health monitoring. The HMS system will provide Wi-Fi and w ...

    STTR Phase II 2019 Department of DefenseNavy
  7. Additive Manufacturing for Naval Aviation Battery Applications

    SBC: Texas Research Institute, Austin, Inc.            Topic: N18AT008

    Texas Research Austin (TRI-Austin) will continue to partner with the University of Texas, Austin, to use additive manufacturing for fabricating and optimizing the lithium ion and electroactive metal electrode systems for which the team established proof of concept in the Phase I base period. The Aerosol Deposition Method (ADM) is a broadly applicable additive manufacturing technology that has been ...

    STTR Phase II 2019 Department of DefenseNavy
  8. Integrated learning-based and regularization-based super resolution for extreme MWIR image enhancement

    SBC: OPTO-KNOWLEDGE SYSTEMS INC            Topic: N17AT016

    OKSI and Northwestern University propose to develop a single-image super-resolution (SR) methodology for mid-wave infrared (MWIR) imagery that combines learning-based and regularization-based approaches to produce extreme enhancement of low-resolution images. We will also develop a detector-limited imaging system specifically designed to be used with the SR methodology for which even higher levels ...

    STTR Phase II 2019 Department of DefenseNavy
  9. Cognitive Adaptation and Mission Optimization (CAMO) for Autonomous Teams of UAS Platforms

    SBC: OPTO-KNOWLEDGE SYSTEMS INC            Topic: N17BT035

    The Navy needs cognitive control capabilities that enable an autonomous robotic team comprised of a ground control station node and a team of UAS platforms to operate independently (or with minimal human oversight) while carrying out complex missions. A cognitive control capability needs to be developed that concurrently optimizes the balance of mission risk / performance with respect to the Navy ...

    STTR Phase II 2019 Department of DefenseNavy
  10. Detect and Avoid Certification Environment for Unmanned Air Vehicles (UAVs)

    SBC: RDRTEC INCORPORATED            Topic: N18AT007

    The objective of this project is to develop a comprehensive suite of tools, called the DAA Radar Software Suite and Simulation (DAA-RSSS), that supports future Navy procurement and certification of non-cooperative sensor technologies for Detect And Avoid (DAA) as well as develop plans to support EO/IR sensors as the non-cooperative sensor as informed by FAA activities in developing Minimum Operati ...

    STTR Phase II 2019 Department of DefenseNavy
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