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Award Data

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The Award database is continually updated throughout the year. As a result, data for FY22 is not expected to be complete until September, 2023.

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.

  1. Improved Identification of the function of Novel and Partially Occluded Laboratory Equipment

    SBC: Novateur Research Solutions, LLC            Topic: DTRA19B002

    This STTR Phase II project proposes development of a statistical relational learning framework for identification of the function of laboratory equipment from imagery. The proposed framework uses semantic reasoning to incorporate evidence from multiple classifiers and feature extractors, domain knowledge, and scene context for scene understanding and labeling. The Phase II effort will focus on dev ...

    STTR Phase II 2021 Department of DefenseDefense Threat Reduction Agency
  2. Multi-Platform 3D Radiation Mapping with Enhanced Sensor Data Fusion and Visualization

    SBC: Gamma Reality Inc.            Topic: DTRA192005

    GRI will develop the capability to fuse 3D map and radiation data from multiple 3D radiation mapping systems in real-time into a single, cohesive global map of an operating environment. This new capability will automatically fuse 3D map and radiation data from the GRI Localization and Mapping Platform (LAMP) systems on ground vehicles and unmanned aerial systems (UASs). This capability will be bui ...

    SBIR Phase II 2021 Department of DefenseDefense Threat Reduction Agency
  3. Computer Vision Image Interpretation for 3D Model Reconstruction

    SBC: TOYON RESEARCH CORPORATION            Topic: DTRA18B001

    Toyon Research Corporation (Toyon) and the University of California, Santa Barbara (UCSB) propose research, development, and demonstration of algorithms and an efficient software prototype for 3D model reconstruction using single images collected via remote sensing. In particular, the effort is focused on processing of high-resolution commercial satellite images for 3D reconstruction of buildings. ...

    STTR Phase II 2021 Department of DefenseDefense Threat Reduction Agency
  4. Compact Laser Drivers for Photoconductive Semicond

    SBC: Scientific Applications & Research Associates, Inc.            Topic: DTRA16A004

    For effective protection against radiated threats, it is important to understand not only the physics of the threats, but also to quantify the effects they have on mission-critical electrical systems. Radiated vulnerability and susceptibility testing requires delivery of high peak power and peak electric fields to distant targets. The most practical solution to simulate such environments on large ...

    STTR Phase II 2018 Department of DefenseDefense Threat Reduction Agency
  5. Bioinformatics: Data Integration for Biomonitoring Applications

    SBC: Arete Associates            Topic: DTRA162002

    Aret Associates and Oak Ridge National Laboratory (ORNL) propose an interdisciplinary effort to further develop and validate a robust, operational biomonitoring application that can process soil microbiome data to reliably detect episodic and low-level chronic contamination while maintaining low false alarm rate.The Phase II SBIR work will build upon the successful Phase I proof-of-concept demonst ...

    SBIR Phase II 2018 Department of DefenseDefense Threat Reduction Agency
  6. A Compact and Fast Long-Wave Infrared (LWIR) Spectroscopy System for Aerosol Combustion

    SBC: OPTICSLAH, LLC            Topic: DTRA182003

    We propose developing new instrumentation based on swept-wavelength external cavity quantum cascade lasers (swept-ECQCLs), to acquire physical/chemical data on chemical weapon agent (CWA) and simulant properties in laboratory-scale explosive testing, and to improve/validate computational fluid dynamics (CFD) codes. In Phase I, we demonstrated laboratory measurements of CWA simulant combustion usin ...

    SBIR Phase II 2021 Department of DefenseDefense Threat Reduction Agency
  7. Innovative Mitigation of Radiation Effects in Advanced Technology Nodes

    SBC: Microelectronics Research Development Corporation            Topic: DTRA16A003

    Micro-RDC has developed portable radiation effects test structures that scale to new process nodes.These structures will enable the investigation of the effects of radiation on the new technology from the material processing level as well as the circuit level.Fabricating the chosen structures and the refinement of software to extract the model parameters will be completed in this effort.A suite of ...

    STTR Phase II 2018 Department of DefenseDefense Threat Reduction Agency
  8. Development of Camera-Motion Insensitive Dynamic Digital Photogrammetry Using Digital Image Correlation

    SBC: TOYON RESEARCH CORPORATION            Topic: DTRA192007

    Toyon will develop and deliver a software prototype implementing algorithms for 3D/4D reconstruction using high-speed-camera and navigation data collected by two UAVs. We will test the software in conditions including both small and larger scenes with collection of ground truth data for moving scenes. We will perform multiple airborne data collections with two UAVs carrying high-speed cameras and ...

    SBIR Phase II 2021 Department of DefenseDefense Threat Reduction Agency
  9. Application of Ultra-Low Cost Differential Pressure Sensors to the Large N Acoustic Sensor Problem

    SBC: TDA Research, Inc.            Topic: DTRA172001

    TDA Research, Inc. (TDA), designed, built, and tested a dense array of 100 very low cost infrasonic sensors. Due to their low cost (1/100x-1/10x the cost of other infrasound sensors), they can be economically deployed in very large numbers; such large arrays can gather more information than a few expensive sensors. They are sensitive from 0.1 Hz - 100 Hz down to 0.08 Pa. We tested the sensors in s ...

    SBIR Phase II 2019 Department of DefenseDefense Threat Reduction Agency
  10. DLeN: Deep Learning for standoff detection of Special Nuclear Material

    SBC: CLOSTRA INC            Topic: DTRA162001

    Deep Learning for standoff detection of Special Nuclear Material (DLeN) applies the same deep learning techniques that allow computers to beat human performance in image recognition and the game of Go to detecting Special Nuclear Material. Spectral analysis and signal processing can in some cases be augmented by the use of much larger neural nets that conduct much deeper analysis of features of th ...

    SBIR Phase II 2018 Department of DefenseDefense Threat Reduction Agency
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