You are here

Award Data

For best search results, use the search terms first and then apply the filters
Reset

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. Cognitive Adaptation and Mission Optimization (CAMO) for Autonomous Teams of UAS Platforms

    SBC: OPTO-KNOWLEDGE SYSTEMS INC            Topic: N17BT035

    OKSI and Professor Matthew Taylor will develop the Cognitive Adaptation and Mission Optimization (CAMO) command and control tool for teams of UAS platforms. CAMO will incorporate existing databases (e.g., NASA population maps, FAA airspace maps, etc.) as well as real-time data from UAS into a learning-based cognitive control solution that maximizes mission performance while minimizing risk for a t ...

    STTR Phase I 2017 Department of DefenseNavy
  2. 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 Navyâ ...

    STTR Phase II 2019 Department of DefenseNavy
  3. Cognitive Risk Management for UAS Missions

    SBC: Stottler Henke Associates, Inc.            Topic: N17BT035

    Enabling operators to command and control multiple UAVs will require higher levels of supervisory control, enabling vehicles to operate autonomously during larger portions of each mission. For the foreseeable future, however, critical portions of each mission will require operators to apply their superior knowledge, judgment, and skills to assess the situation, monitor execution more closely and, ...

    STTR Phase I 2017 Department of DefenseNavy
  4. Compact and Low-cost High Performance Spectrometer Sensor based on Integrated Photonics Technology

    SBC: ULTRA-LOW LOSS TECHNOLOGIES LLC            Topic: N19AT023

    Ultra-Low Loss Technologies (ULL Technologies) is proposing in collaboration with Prof. Arka Majumdar from University of Washington (UW), to develop a compact, low-cost spectrometer module to be used for chemical sensing applications and to be fabricated using the process design kit (PDK) available through AIM Photonics multi-project wafer run (MPW). The team will combine ULL Technologies expertis ...

    STTR Phase I 2019 Department of DefenseNavy
  5. Comprehensive Surf Zone Modeling Tool

    SBC: Arete Associates            Topic: N19AT010

    Areté Associates, along with STTR partner Rochester Institute of Technology (RIT), are proposing a comprehensive software capability for scene generation, object insertion, and performance modeling for passive and active EO COBRA sensors over the surf zone. The Surf Zone Modeling Tool (SZT) will incorporate several technologies, including: open-source and Areté-designed SZ ocean physics models, ...

    STTR Phase I 2019 Department of DefenseNavy
  6. Conjugate heat transfer for LES of gas turbine engines

    SBC: CASCADE TECHNOLOGIES INC            Topic: N19BT027

    Current design tools for gas turbine engines invoke a variety of simplifying assumptions to estimate heat transfer to solid/metal engine components (e.g., isothermal boundary conditions). These approximations are often not valid, result in inaccurate predictions of heat transfer, and ultimately compromise the thermal integrity of propulsion and power systems. Wall-modeled large eddy simulation (WM ...

    STTR Phase I 2019 Department of DefenseNavy
  7. 3D Acoustic Model for Geometrically Constrained Environments

    SBC: HEAT, LIGHT, AND SOUND RESEARCH, INC.            Topic: N16AT018

    Systems that operate in constrained environments depend on the acoustics in several ways. Harbor defense systems detect intruders (people and/or vessels) by either listening for their noises (passively) or by pinging on them and detecting their echoes (actively). Furthermore, such systems may also form the equivalent of an underwater cell phone network using sound to carry the information. The aco ...

    STTR Phase I 2016 Department of DefenseNavy
  8. 3D Acoustic Model for Geometrically Constrained Environments

    SBC: HEAT, LIGHT, AND SOUND RESEARCH, INC.            Topic: N16AT018

    Systems that operate in constrained environments depend on the acoustics in several ways. Harbor defense systems detect intruders (peopleand/or vessels) by either listening for their noises (passively) or by pinging on them and detecting their echoes (actively). Furthermore, suchsystems may also form the equivalent of an underwater cell phone network using sound to carry the information. The acous ...

    STTR Phase II 2017 Department of DefenseNavy
  9. Data Science Techniques for Various Mission Planning Processes and Performance Validation

    SBC: Perceptronics Solutions, Inc.            Topic: N19BT029

    Mission and planning is a difficult and time-consuming process that places a heavy burden on manpower and critical thinking and is performed under significant pressure. Existing and emerging artificial intelligence (AI) and machine learning (ML) techniques are well-suited to assisting humans with these challenges. While the promise of AI/ML is great, there are significant obstacles to operationali ...

    STTR Phase I 2019 Department of DefenseNavy
  10. Degraded Synthetic Training Using an Integrated Kinetic-Cyber Training Environment

    SBC: Scalable Network Technologies, Inc.            Topic: N17AT023

    Integration of kinetic training and cyber training will provide a unified platform for combined cyberspace/kinetic battlefield training for our warfighters. Such a training platform will support high-fidelity, multi-factor simulated engagements in which the trainee can be exposed to all domains that are simultaneously interacting with each other. Existing approaches do not accurately reflect the d ...

    STTR Phase I 2017 Department of DefenseNavy
US Flag An Official Website of the United States Government