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 June, 2020.

  1. N/A

    SBC: ECOPULSE            Topic: N/A

    N/A

    SBIR Phase I 2000 Department of DefenseDefense Threat Reduction Agency
  2. HOLOGRAPHIC PATTERN RECOGNITION FOR ARMS CONTROL

    SBC: EMPIRICAL TECHNOLOGIES CORPORATION            Topic: N/A

    THE CONTRACTOR HAS PATENTED TECHNOLOGY FOR A UNIQUE PROCESS THAT DIRECTLY CONVERTS AN ACOUSTIC SIGNAL INTO A VISIBLE ONE IN REAL-TIME WITHOUT ELECTRONIC CIRCUITRY. THIS RELIES ON THE ACOUSTO-OPTICAL PROPERTIES OF A CONTINUOUS LAYER OF LIQUID CRYSTAL THIN FILM LAYER WHICH SERVES AS BOTH THE SENSOR AND THE DISPLAY. THE IMAGE CAN BE VIEWED DIRECTLY BY MEANS OF CCD CAMERA. HOLOGRAPHY PROVIDES FOR BOTH ...

    SBIR Phase I 1990 Department of DefenseDefense Threat Reduction Agency
  3. N/A

    SBC: Prime Photonics, Inc.            Topic: N/A

    N/A

    SBIR Phase I 2000 Department of DefenseDefense Threat Reduction Agency
  4. N/A

    SBC: Harris Technologies LLC            Topic: N/A

    N/A

    SBIR Phase I 2000 Department of DefenseDefense Threat Reduction Agency
  5. Heterdyne Interferometer for Triggering Gas Puff PRSs

    SBC: HY-Tech Research Corp.            Topic: N/A

    Large X-ray generators using gas fill loads are a key element in the DTRA simulator program. Consistent relative timing between the injection of the gas shell and the generator current pulse is crucial to producing consistent, high-yield x-ray pulses.To that end HY-Tech proposes replacing existing high voltage trigger pin technology, with a sensitive, all fiber-optic heterodyne interferometer ba ...

    SBIR Phase I 2003 Department of DefenseDefense Threat Reduction Agency
  6. SNAPSHOT: A System for Predicting Human Physical Traits from Sample DNA

    SBC: PARABON NANOLABS, INC.            Topic: DTRA102007

    OBJECTIVE: Develop a Forensic DNA Analysis Kit for Genetic Intelligence that can be used on unknown human DNA samples collected from the battlefield to provide information about the individual who deposited the sample, such as potential ethnicity, height, eye color, hair color, age, sex, and/or facial features. The kit should leverage Short Tandem Repeats (STR), Single Nucleotide Polymorphisms (S ...

    SBIR Phase I 2011 Department of DefenseDefense Threat Reduction Agency
  7. Numerical Model of Subsurface Transport of Noble Gases in Fractured Geologic Media for Detection and Identification of Subsurface Nuclear Explosion Te

    SBC: MODERN TECHNOLOGY SOLUTIONS, INC.            Topic: DTRA111002

    Surface detection of specific radioisotopes of the noble gases xenon and argon are essential for detection and discrimination of underground nuclear explosions. We propose a unique combination of numerical modeling and stable isotope release experiments to enhance the predictability of subsurface transport of the noble gases of interest. Our proposed research will identify and quantify the physi ...

    SBIR Phase I 2011 Department of DefenseDefense Threat Reduction Agency
  8. HybridSil Nanocomposite Potting Materials for Next Generation Precision Munitions

    SBC: Nanosonic Inc.            Topic: DTRA112001

    The objective of this SBIR program is to adapt NanoSonic"s high temperature, ballistic resistant HybridSilTM nanocomposites for use as next generation potting materials with exceptional thermal durability, g-force resilience, and negligible variation (

    SBIR Phase I 2012 Department of DefenseDefense Threat Reduction Agency
  9. Adaptable Multi-Layer Inference System for Distributed Sensor Networks

    SBC: ADAPTIVE METHODS, INC.            Topic: DTRA112002

    Adaptive Methods and Applied Research Laboratory at Penn State are developing a hierarchical inference approach for multi-modal unattended ground sensor (UGS) networks. that will enable significant performance gains via integrated machine learning techniques, to include In situ performance characterization and automated adaptation to site-specific environmental characteristics; unsupervised learni ...

    SBIR Phase I 2012 Department of DefenseDefense Threat Reduction Agency
  10. Automated pattern recognition methods to identify nuclear explosions

    SBC: Acorn Science & Innovation, Inc.            Topic: DTRA182005

    Reliable automated pattern recognition in the current system is limited by excessive noise and clutter combined with insufficient and/or ambiguous features. Our team consisting of AcornSI and Leidos thus propose a multi-step approach based on the combined effects of improved detection, feature extraction, phase identification, and global association.A key innovation here is creating a new classifi ...

    SBIR Phase I 2019 Department of DefenseDefense Threat Reduction Agency
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