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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. Techniques to Adjust Computational Trends Involving Changing Data (TACTIC-D)

    SBC: OASYS, INC.            Topic: N17BT032

    The Navy seeks technology based on statistical or computational methods to assist in the continued tracking of training performance and proficiency trends as underlying tactical data changes. OASYS, INC. and the ITCS at UAH proposes to exploit the benefits of modeling the underlying cause-effect structure of Navy data, rather than the data itself. This approach makes the model and analytical metho ...

    STTR Phase I 2017 Department of DefenseNavy
  2. Risk-Based Unmanned Air System (UAS) Mission Path Planning Capability

    SBC: ACTA, LLC            Topic: N17BT034

    In this Phase I Project ACTA and its partners will demonstrate the feasibility of developing a risk-based mission path planning (RB MPP) approach. Areas of interest to the Navy where a RB MPP address critical needs include enabling less restrictive UAS operations within the US National and Foreign Airspaces. The Phase I will demonstrate feasibility with a two-step approach. The first step will dem ...

    STTR Phase I 2017 Department of DefenseNavy
  3. 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
  4. 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
  5. 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 super-resolution (SR) methodology for mid-wave infrared (MWIR) imagery that produces extreme enhancement of low resolution images. Image enhancement of at least 4x is expected using a standard imaging system. OKSI and Northwestern University will also develop a detector-limited imaging system specifically designed to be used with the SR methodo ...

    STTR Phase I 2017 Department of DefenseNavy
  6. High Density Capacitors for Compact Transmit and Receive Modules

    SBC: Bioenno Tech, LLC            Topic: N17AT011

    Development of a new generation of high-energy-density capacitors for power conversion/conditioning systems will be beneficial to reduce the size, weight, and cost of resultant transmit and receive (T/R) modules in modern radar and electronic warfare transmitters. Among capacitor technologies available, multilayer ceramic capacitors (MLCCs) and polymer-ceramic composite dielectric based capacitors ...

    STTR Phase I 2017 Department of DefenseNavy
  7. Transformation Accelerated through Redesign, Guidance, and Enhanced Training (TARGET)

    SBC: TIER 1 PERFORMANCE SOLUTIONS LLC            Topic: N17AT017

    As submarine threats from adversary countries continue to rise, the U.S. Navy must maintain and expand its anti-submarine warfare (ASW) capabilities. Warfighter readiness is the linchpin of the Navys ASW strategy, but the complexity of the ASW domain necessitates time-consuming training, and practical experiences to transfer those skills to the operational environment. An innovative training appro ...

    STTR Phase I 2017 Department of DefenseNavy
  8. Phase-Change Materials for Tunable Infrared Devices

    SBC: Sensormetrix, INC            Topic: N17AT020

    The proposed Phase I research seeks to develop innovative tunable IR filters based on phase change plasmonic composite materials. Concepts for a switchable device that is capable of providing dynamic narrowband spectral properties within the 3-12 micron wavelength range will be developed.

    STTR Phase I 2017 Department of DefenseNavy
  9. Video and Audio Data Extraction for Retrieval, Ranking, and Recapitulation

    SBC: ONAI INC.            Topic: N17AT021

    We propose a multi-part system to process, understand, and summarize video streams. Our approach involves processing video and audio jointly; uses the latest advances in captioning and automatic speech-recognition to construct text narratives for the video; and uses NLP techniques to summarize and produce a reliable relevance ranking of these videos. We address all six technical challenges identif ...

    STTR Phase I 2017 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
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