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Award Data

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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. Virtual Reality for Multi-INT Deep Learning (VR-MDL)

    SBC: INFORMATION SYSTEMS LABORATORIES INC            Topic: AF19AT010

    Recent advances and successes of deep learning neural networks (DLNN) techniques and architectures have been well publicized over the last several years. Voluminous, high-quality and annotated training data, or trial and error in a realistic environment, is required to achieve the promised performance potential of DLNNs. Unfortunately for DoD and/or Intelligence Community (IC) applications of mult ...

    STTR Phase I 2019 Department of DefenseAir Force
  2. Multiphysics Modeling of Dynamic Combustion Processes Using Pareto-Efficient Combustion Framework

    SBC: STREAMLINE NUMERICS, INC.            Topic: AF18BT010

    The objective is to develop zonal multi-physics capability for turbulent combustion simulations. The foundation of the proposed work is a novel Pareto-Efficient Combustion (PEC) framework for fidelity-adaptive combustion modeling. The PEC model utilizes a combustion submodel assignment, combining the low-cost flamelet-based models with the more expensive finite rate chemistry models where necessar ...

    STTR Phase I 2019 Department of DefenseAir Force
  3. CogTracer

    SBC: SOAR TECHNOLOGY, LLC            Topic: AF18BT001

    From individualized training, to responsive decision-support, and improved human-machine teaming, the ability to accurately predict the cognitive state of an individual in real time would open the door for numerous technologies that would benefit the operational needs of the warfighter. Until now, much of the research using EEG for operational needs has focused on tailoring a system to detect only ...

    STTR Phase I 2019 Department of DefenseAir Force
  4. 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
  5. Enhanced Sensor Resource Management Utilizing Bayesian Inference

    SBC: GCAS INC            Topic: N19AT002

    This proposal describes the use of machine learning, data mining and Bayesian inference algorithms for incorporation into a surveillance aircraft cognitive radar system. The need for incorporation of higher-order uncertainty distributions will also be assessed. This will result in enhanced sensor resource management capability for surveillance aircraft radar.

    STTR Phase I 2019 Department of DefenseNavy
  6. Improving Analysis of Large Multidimensional Data through Parallel Processing & Explorative Visualization

    SBC: FRONTIER TECHNOLOGY INC.            Topic: MDA18T001

    Using a combination of parallel processing and explorative visualization, a new and exciting solution for high-performance visual analysis of large multidimensional data is proposed. Steady volume flows are selected to demonstrate the strategy, methodology, techniques, and functionalities. Virtual Reality (VR) and Augmented Reality (AR) platforms will be adopted to unleash the power of explorative ...

    STTR Phase I 2019 Department of DefenseMissile Defense Agency
  7. 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
  8. Predictive Graph Convolutional Networks

    SBC: ARETE ASSOCIATES            Topic: N19AT017

    The US Navy’s mission to maintain, train and equip combat-ready Naval forces requires that decision makers have situational awareness of the capabilities, limitations, vulnerabilities/opportunities for adversarial and allied forces. An incomplete or inaccurate understanding of the current landscape and associated trends could lead to suboptimal mission readiness and outcomes. Analysts need tools ...

    STTR Phase I 2019 Department of DefenseNavy
  9. Atomic Triaxial Magnetometer

    SBC: VESCENT TECHNOLOGIES INC.            Topic: N19AT006

    Vescent Photonics and MIT Lincoln Labs (MIT-LL) propose to develop a quantum-based vector magnetometer with low size, weight, power, and cost (SWaP+C) for Navy applications. The proposed system will rely on probing magnetically-sensitive, atomic-like transitions of nitrogen-vacancy (NV) centers in diamond to provide stable, high-bandwidth readout of the vector magnetic field with sub-picotesla sen ...

    STTR Phase I 2019 Department of DefenseNavy
  10. Carbon Nanotube Based Monolithic Millimeter-wave Integrated Circuits

    SBC: ATOMINC INC            Topic: A18BT004

    In this project, we propose to develop a high-performance carbon nanotube (CNT) based millimeter-wave transistor technology and demonstrate monolithic millimeter-wave integrated circuits (MMICs) based on this technology with improved power efficiency, linearity, noise and dynamic range performance over existing GaAs, SiGe and RF-CMOS technologies. The goal of this topic is to leverage Professor St ...

    STTR Phase I 2019 Department of DefenseArmy
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