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 FY20 is not expected to be complete until September, 2021.

  1. Optimization of Fatigue Test Signal Compression Using the Wavelet Transform

    SBC: ATA Engineering, Inc.            Topic: N18BT029

    Traditional approaches to accelerated fatigue testing rely on heuristic methods with thresholds based mostly on experience and engineering judgment. These methods generally do not apply to the multiaxial dynamic loading situations characteristic of most aerospace applications and often result in uncharacteristic fatigue damage and failure modes during testing. To overcome the limitations of tradit ...

    STTR Phase I 2018 Department of DefenseNavy
  2. 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
  3. 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
  4. An Integrated Materials Informatics/Sequential Learning Framework to Predict the Effects of Defects in Metals Additive Manufacturing

    SBC: Citrine Informatics, Inc.            Topic: N18AT013

    In this project, Citrine Informatics and the ADAPT Center at the Colorado School of Mines propose to build an informatics-driven system to understand the effects of defects in additive manufactured parts. The entire history of each sample will be captured on this system; from specific printing parameters and details of precursor materials through to part characterizations and performance measureme ...

    STTR Phase I 2018 Department of DefenseNavy
  5. Power and Propulsion System Optimization

    SBC: Cornerstone Research Group, Incorporated            Topic: N18AT012

    Unmanned underwater vehicles (UUVs) are currently limited in the type of missions they can perform. Limited available power limits which sensors can be run or for how long, and also limits the duration and range of the mission. More efficient propulsion systems would increase the power available to the UUV payload. Improved power distribution systems and control systems would also increase the ava ...

    STTR Phase I 2018 Department of DefenseNavy
  6. Compact Thermal Management System for Laser Systems

    SBC: Spectral Energies, LLC            Topic: N18AT001

    The use of laser technologies and high-power electronics is rapidly being incorporated into tactical platforms for imaging, target designation, and range finding. Electronic equipment including lasers demand power from a tactical aircraft and produce large amounts of thermal energy as a waste product. Current thermal management technologies will not be sufficient for future aircraft as thermal man ...

    STTR Phase I 2018 Department of DefenseNavy
  7. Full Featured Low-Cost HMS for Combatant Craft

    SBC: QUALTECH SYSTEMS, INC.            Topic: N18AT015

    Qualtech Systems, Inc. (QSI), in collaboration with VU proposes to develop a state-of-the art HMS system featuring: (1) Low Hardware cost by leveraging industrial-grade computers ruggedized to military specifications (2) Low Software cost by leveraging QSI’s COTS TEAMS software with real-time monitoring and diagnosis capabilities (3) Vibration and Shock Analysis and its impact on vehicle and cre ...

    STTR Phase I 2018 Department of DefenseNavy
  8. Active Imaging through Fog

    SBC: SA Photonics, Inc.            Topic: N18AT021

    Active imaging systems are used to for imaging in degraded visual environments like that found in marine fog and other environments with a high level of attenuation and scattering from obscurants like fog, rain, smoke, and dust.These systems are still limited in range and resolution. SA Photonics is taking advantage of multiple image enhancement techniques, like wavelength tunability, pulse contro ...

    STTR Phase I 2018 Department of DefenseNavy
  9. Control & Optimization of Multiple Illumination Characteristics (COMIC) of A Pulsed Fiber Array Laser System For Active Imaging Through Fog

    SBC: MV Innovative Technologies LLC (DBA: Opt            Topic: N18AT021

    Degraded weather conditions particularly, dense maritime fog, reduces the US Fleet EO/IR systems ability to maintain situational awareness and detect/identify and track targets of interest. It is the Navys goal to develop an active EO/IR imaging system that jointly optimizes illumination source properties and implements advanced image processing to improve performance and operational range of curr ...

    STTR Phase I 2018 Department of DefenseNavy
  10. Internet of Things (IoT) Agent (IoTA) Framework for Evaluating Effectiveness and Efficiency

    SBC: RAM LABORATORIES            Topic: N18AT027

    The Internet of Things (IoT) is increasingly being used to create smart platforms where operators are being removed from the loop. These smart capabilities include collaborative IoT sensors and platforms that are self-aware and provide capabilities of self-prediction, self-configuration, and self-maintenance. To fully take advantage of these advances, however, testbeds and frameworks are needed to ...

    STTR Phase I 2018 Department of DefenseNavy
US Flag An Official Website of the United States Government