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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. Dim Target Extraction and Conjoint Tracking (DTECT) Enhancements for Missile Defense Applications

    SBC: TOYON RESEARCH CORPORATION            Topic: MDA12T004

    Overhead Persistent Infrared (OPIR) platforms observe challenging threat and scene phenomenology. Toyon Research Corporation developed an image processing framework for clutter estimation/suppression and track-before-detect to jointly detect and track targets. The Target Extraction and Conjoint Tracking application, developed under initial Phase II funding and demonstrated using real-world data so ...

    STTR Phase II 2017 Department of DefenseMissile Defense Agency
  2. Programmable Multi-Frequency Transmitter for Missile Communciations

    SBC: Space Micro Inc.            Topic: MDA16T005

    Improving capabilities of telemetry systems for next generation e.g. (MOKV) missile defense launch vehicles, kill vehicles, and test/target vehicles subsystems can transform operational testing of such systems and has the potential to increase capabilities of systems that rely on radio communications. As these systems, and their test scenarios become get more complex they will require unprecedente ...

    STTR Phase II 2018 Department of DefenseMissile Defense Agency
  3. Deep Learning with Whole-Scene Contextual Reasoning for Target Characterization

    SBC: EXOANALYTIC SOLUTIONS INC            Topic: MDA15T001

    ExoAnalytic Solutions is developing DEEPR (Deep Learning with Whole-Scene Contextual Reasoning for Object Characterization), an advanced multi-sensor multi-object classifier for integrated object characterization. The overall objective of DEEPR is to develop a suite of advanced, novel techniques that combine innovative advances in deep, hierarchical machine learning together with recurrent Deep L ...

    STTR Phase II 2017 Department of DefenseMissile Defense Agency
  4. SmallSat Stirling Cryocooler for Missile Defense (SSC-X)

    SBC: WECOSO, INC.            Topic: MDA17T003

    West Coast Solutions (WCS), in collaboration with the Georgia Institute of Technology and Creare LLC, proposes an adaptation of our SmallSat Stirling Cryocooler (SSC) technology in response to STTR Topic MDA17-T003: High-Efficiency, Low-Volume, Space-Qualified Cryogenic-Coolers. In Phase 1 we will scale up a design currently in development for NASA to meet the Missile Defense Agency (MDA) topic re ...

    STTR Phase I 2018 Department of DefenseMissile Defense Agency
  5. Lightweight Structural Components of a Missile Body

    SBC: ALPHASTAR TECHNOLOGY SOLUTIONS LLC            Topic: MDA17T004

    The Ground-Based Interceptor (GBI) missile is the weapon component of the Ground-Based Midcourse Defense (GMD) system that consists of a rocket booster and kinetic kill vehicle. Recently, MDA has sought technologies to improve the performance of the booster vehicle (BV). To date, studies have shown that reductions in weight have a direct impact on overall effectiveness. The current proposal aims t ...

    STTR Phase I 2018 Department of DefenseMissile Defense Agency
  6. Hybrid DNN-based Transfer Learning and CNN-based Supervised Learning for Object Recognition in Multi-modal Infrared Imagery

    SBC: TOYON RESEARCH CORPORATION            Topic: 1

    On this effort Toyon Research Corp. and The Pennsylvania State University are developing deep learning-based algorithms for object recognition and new class discovery in look-down infrared (IR) imagery. Our approach involves the development of a hybrid classifier that exploits both transfer learning and semi-supervised paradigms in order to maintain good generalization accuracy, especially when li ...

    STTR Phase I 2018 Department of DefenseNational Geospatial-Intelligence Agency
  7. Algorithms for Look-down Infrared Target Exploitation

    SBC: SIGNATURE RESEARCH, INC.            Topic: 1

    Signature Research, Inc. (SGR) and Michigan Technological University (MTU) propose a Phase I STTR effort to develop a learning algorithm which exploits the spatio-spectral characteristics inherent within IR imagery and motion imagery.Our archive of modelled and labeled data sets will allow our team to thoroughly capture the variable elements that will drive machine learning performance.The overall ...

    STTR Phase I 2018 Department of DefenseNational Geospatial-Intelligence Agency
  8. Green Monopropellant Thruster Technology Maturation

    SBC: BUSEK CO., INC.            Topic: AF151066

    Busek, with its Small Business Technology Transfer partner Sandia National Laboratory (SNL), proposes to undertake the development of a AF-M315E green monopropellant thruster for a potential flight application. Busek will be designing, fabricating, and qualifying the thruster to Technology Readiness Level (TRL) 5 status. SNL will be performing additional qualification tests for Busek and perfor ...

    STTR Phase II 2017 Department of DefenseMissile Defense Agency
  9. System for Nighttime and Low-Light Face Recognition

    SBC: Systems & Technology Research LLC            Topic: SOCOM18A001

    Face recognition performance using deep learning has seen dramatic improvements in recent years. This improvement has been fueled in part by the curation of large labeled training datasets with millions of images of hundreds of thousands of subjects.This results in effective generalization for matching over pose, illumination, expression and age variation, however these datasets have traditionally ...

    STTR Phase I 2018 Department of DefenseSpecial Operations Command
  10. Human Performance Optimization: Ketone Esters for Optimization of Operator Performance in Hypoxia

    SBC: HVMN Inc.            Topic: SOCOM17C001

    In the setting of altitude-induced hypoxia, operator cognitive capacity degrades and can compromise both individual and team performance. This degradation is linked to falling brain energy (ATP) levels and an increased reliance on anaerobic energy production from glucose. Ketone bodies are the evolutionary alternative substrate to glucose for brain metabolic requirements; previous studies have sho ...

    STTR Phase I 2018 Department of DefenseSpecial Operations Command
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