Award Data

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The Award database is continually updated throughout the year. As a result, data for FY19 is not expected to be complete until September, 2020.

  1. Electromagnetic Fields and Effects Inside Aircraft Cabins, Cockpits, and Avionics Bays

    SBC: Hypercomp, Inc.            Topic: N182107

    HyPerComps proposed effort will specifically address the following NAVAIR requirements: A method is contributing new ideas and innovations in both time-domain and frequency domain computational electromagnetics (CEM), especially in addressing accuracy and scalability for large-scale modeling of EM fields inside and around complex cavities, and computational efficiency for quick turnaround for freq ...

    SBIR Phase I 2018 Department of DefenseNavy
  2. Photonic Integrated Circuit Reliability Modeling Methodology to Enable Standardization

    SBC: Intelligent Fiber Optic Systems Corporation            Topic: N182108

    The DoD S&T communitys understanding of photonic integrated circuit (PIC) and related Planar Lightguide Circuit (PLC) reliability has gaps preventing full PIC deployment to defense avionics. Validation of PIC reliability is critical to enabling rapid transition to DoD programs. IFOS is leveraging its proven expertise in PIC-based systems to develop PIC reliability prediction models. We will levera ...

    SBIR Phase I 2018 Department of DefenseNavy
  3. Photonic Integrated Circuit Reliability Prediction, Verification and Validation

    SBC: Freedom Photonics LLC            Topic: N182108

    Photonic Integrated Circuits (PICs) and Planar Lightguide Circuits (PLCs) are finding application in optical communication and sensor systems for both military and commercial applications. The reliability of PIC and PLC devices applicable to Department of Defense (DoD) avionics, sensors, and electronic warfare is largely unknown. Verification and validation of PIC and PLC device reliability is par ...

    SBIR Phase I 2018 Department of DefenseNavy
  4. Multicore Fiber Optic Packaged Photonic Integrated Circuits for Wideband RF over Fiber

    SBC: Freedom Photonics LLC            Topic: N182101

    In this program, Freedom Photonics intend to explore the new approaches to the balanced photodiode implementation, to obtain and verify a design that meets the Navys requirements, to develop multicore fiber coupling technology for photonic integrated circuits (PIC), and to leverage our expertise in PIC design, fabrication and packaging to produce a rugged final prototype, suitable for production. ...

    SBIR Phase I 2018 Department of DefenseNavy
  5. Propellant Health Monitoring System

    SBC: Intellisense Systems, Inc.            Topic: N182111

    To address the Navy need for a sensor capable of detecting cracks in propellant grain and transmitting the sensor data wirelessly through a hermetically sealed rocket motor case, Intellisense Systems, Inc. (ISI) proposes to develop a new Propellant Health Monitoring (PHEM) system, based on the novel integration of ultrasonic transducers as both signal generator and sensor with ultralow-power compo ...

    SBIR Phase I 2018 Department of DefenseNavy
  6. Wireless Multi-Point Fiber Optic Acoustic-Ultrasound Propellant Grain Cracks Detection System

    SBC: Redondo Optics, Inc.            Topic: N182111

    Redondo Optics Inc. proposes to develop and demonstrate to the Navy a miniature, lightweight, and low power, wireless multi-point fiber optic acoustic-ultrasound sensor (FAULT) SHM system suitable for the in-situ, real-time, and un-attended detection, identification, localization, and classification of suitable for the un-invasive, in-situ, real-time, and un-attended detection, identification, loc ...

    SBIR Phase I 2018 Department of DefenseNavy
  7. Oceanography Tactics Training for Employment Readiness

    SBC: Ocupath LLC            Topic: N182119

    Project OAR (Oceanographic Augmented Reality) is a software-based tool that leverages embodied cognition with augmented and virtual reality to create highly engaging and impactful oceanographic training. With OAR, trainees will see oceanographic animated behaviors up close and from several angles to help ensure learning. The project brings together education researchers, software developers, and o ...

    SBIR Phase I 2018 Department of DefenseNavy
  8. 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
  9. Hybrid DNN-based Transfer Learning and CNN-based Supervised Learning for Object Recognition in Multi-modal Infrared Imagery


    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
  10. 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
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