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The Award database is continually updated throughout the year. As a result, data for the given year is not complete until April of the following year. Annual Reports data is a snapshot of agency reported information for that year and hence might look different from the live data in the Awards Information charts.

  1. AI-based Endpoint Defender (ABED)

    SBC: Assured Information Security, Inc.            Topic: AF173002

    Existing endpoint defense solutions often rely on file signature blacklists and patterns derived from static analysis. These techniques, while proficient at mitigating the specific threats they are designed to detect, offer little protection against modern file and document formats that allow for the embedding of arbitrary data.AIS proposes ABED to detect and prevent malware and exploits in less t ...

    SBIR Phase I 2018 Department of DefenseAir Force
  2. Lithium Metal or Lithium-ion (Li-ion) Battery using Nonflammable, Room-Temperature Ionic Liquid or Solid Electrolyte(s)

    SBC: NOHMS Technologies, Inc.            Topic: AF173005

    NOHMs Technologies proposes to develop non-flammable, highly conductive ionic liquid-hybrid electrolytes that overcome safety concerns in Li-ion batteries. These electrolytes operate over a wide temperature range, and are electrochemically stable to ensure long battery lifetimes. The proposed technology is based on innovative functional ionic liquid hybrid materials developed by NOHMs Technologies ...

    SBIR Phase I 2018 Department of DefenseAir Force
  3. Cross Domain Full Motion Video

    SBC: Trident Systems Incorporated            Topic: AF05093

    At present, there is no cross domain solution that is certified to filter streaming video data.The proposed effort is to develop a Cross Domain Full Motion Video (CD FMV) solution, which will be based on Tridents certified Voice & Video Cross Domain Solution (V2 CDS).The desired end state for the CD FMV technology is a fundamentally new product that leverages Tridents Assured Pipeline and XML filt ...

    SBIR Phase II 2018 Department of DefenseAir Force
  4. Airborne Graph Analytics Applications for Multi-sensor Fusion and Integration

    SBC: BLACK RIVER SYSTEMS COMPANY INC            Topic: AF161131

    Black River Systems will develop a graph based software prototype that will demonstrate the following capabilities: (1) Capturing, maintaining, and updating a graph based representation of device/emitter association ambiguities for an airborne integration and fusion capability for MOVINT kinematic tracks and sparse identification sensor information; (2) An automated real time graph solver that pro ...

    SBIR Phase II 2018 Department of DefenseAir Force
  5. Cognitive Processing and Exploitation of 3D Laser Imaging Detection and Ranging (LIDAR) Imagery Data

    SBC: Novateur Research Solutions, LLC            Topic: AF161138

    This STTR Phase II project will develop a hierarchical visual processing system and attention-based mechanisms based on novel 3D convolutional neural networks to enable robust and efficient detection and classification of objects in 3D LIDAR imagery. The Phase II will build upon the enabling technologies developed in Phase I which, using deep learning methods, model the ventral pathway of the visu ...

    SBIR Phase II 2018 Department of DefenseAir Force
  6. Handheld Dismount Kit for Persistent, Precision Navigation in GPS-challenged Environments for Military Operations

    SBC: Echo Ridge, LLC            Topic: AF153002

    Echo Ridge proposes to deliver quantity three first-generation augmented positioning system (APS) devices to AFRL at the end of the 12-month sequential Phase II effort.The units will be capable of producing accurate PNT estimates in GPS-denied environments in a stand-alone operational mode.The units will include improvements to both the PNT estimation methods and the hardware platform developed an ...

    SBIR Phase II 2018 Department of DefenseAir Force
  7. Operational Outer Zone Energetic Charged Particle Model

    SBC: Space Sciences Innovations INC            Topic: AF17CT03

    The goal of the proposed work is to provide the Air Force with a state-of-the-art model of the outer zone energetic charged particles, including data assimilation capabilities. The UCLA-developed Versatile Electron Radiation Belt (VERB) model will be optimized for various measurements obtained on various satellite orbits by different instruments. We will transfer VERB code to SSI, test and validat ...

    STTR Phase I 2018 Department of DefenseAir Force
  8. Quantum Sensor for Direction Finding and Geolocation

    SBC: HYPRES, INC.            Topic: AF17AT028

    In this STTR phase I, HYPRES and University of California Riverside will demonstrate the feasibility of a three-dimensional electromagnetic (EM) sensor for accurate vector sensing and geo-location of complex RF emitters exploiting the novel quantum electrodynamic properties stemming from innovations in superconducting nanoelectronics specifically in utilizing direct-write, high temperature superco ...

    STTR Phase I 2018 Department of DefenseAir Force
  9. Self-Calibrating, Conformal Nanomembrane based Pressure Sensors for Embedded Sensing Applications

    SBC: Nanosonic Inc.            Topic: AF18AT002

    This Air Force Phase I STTR program would develop self-calibrating, conformal nanomembrane (NM) based pressure sensors for embedded sensing applications, using SOI (Silicon on Insulator) NM techniques in combination with our pioneering nanocomposite materials.Such low-modulus, conformal nanomembrane sensor skins with integrated self-calibration, interconnect elements and electronic devices that ca ...

    STTR Phase I 2018 Department of DefenseAir Force
  10. Application of Hierarchical Memory Models to Automatic Target Recognition Modeling and Simulation

    SBC: Novateur Research Solutions, LLC            Topic: AF18AT014

    This SBIR Phase I project proposes a visual processing system for automated target recognition. Inspired by biological vision systems and hierarchical memory models, the proposed system is capable of learning hierarchical invariant features from unlabeled data that are independent of object labels. The model exploits these learned features to create hierarchical representations of target memories ...

    STTR Phase I 2018 Department of DefenseAir Force

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