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The Award database is continually updated throughout the year. As a result, data for FY24 is not expected to be complete until March, 2025.

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.

The SBIR.gov award data files now contain the required fields to calculate award timeliness for individual awards or for an agency or branch. Additional information on calculating award timeliness is available on the Data Resource Page.

  1. Wash Durable Flame Resistant NonWovens

    SBC: LUNA INNOVATIONS INCORPORATED            Topic: A16AT015

    Luna Innovations, teamed with North Carolina State University’s (NCSU) Non-Wovens Institute (NWI), will meet the Army’s need to develop a novel wash durable, flame resistant, non-woven textile. This practical system will provide military uniforms with excellent flame resistant (FR) protection at a lower manufacturing cost without compromising performance such as durability, repellency, and vec ...

    STTR Phase II 2018 Department of DefenseArmy
  2. Advanced Fire Control Radar for Group 1 and 2 Unmanned Surveillance Systems

    SBC: Physical Optics Corporation            Topic: A17126

    To address the Army’s need for a fire control radar for small UASs, Physical Optics Corporation (POC) proposes to develop an Advanced Fire Control Radar for Group 1 and 2 Unmanned Surveillance Systems (ARGUS). ARGUS is a compact, lightweight, and low power sensor that directly fits in the electronics or payload bay of Group 1 and 2 UASs. It interfaces with the platform’s flight computer throug ...

    SBIR Phase I 2018 Department of DefenseArmy
  3. DEEP FOCUS: USING DEEP LEARNING TO DISCERN TARGETS IN CLUTTERED RADAR

    SBC: CLOSTRA INC            Topic: A17133

    Deep Focus applies deep learning neural nets to Apache Fire Control Radar (FCR) targeting and target identification, with applicability to related systems. Recent innovations in deep learning theory and implementation have enabled neural nets to achieve what was once unthinkable: beat humans at complex image recognition skills, safely pilot cars over chaotic road systems, and overwhelm Grandmaster ...

    SBIR Phase I 2018 Department of DefenseArmy
  4. Fiber Laser with Enhanced Coupling

    SBC: HEDGEFOG RESEARCH INC.            Topic: A17136

    To address the Army’s need for a novel approach that enables pump combiners with improved coupling efficiency for high-power fiber laser systems, Hedgefog Research Inc. (HFR) proposes to develop a new Fiber Laser with Enhanced Coupling (FLEC) that minimizes excess heat generation in fiber lasers via efficient mode scrambling of the pump light in the cladding of the active fiber. Specifically, we ...

    SBIR Phase I 2018 Department of DefenseArmy
  5. Low-Cost Ultra-lightweight CW Detection for Micro UAVs and Other Applications

    SBC: INTELLIGENT OPTICAL SYSTEMS, INC.            Topic: CBD11103

    Building on our established thin-film chemical detection technology, Intelligent Optical Systems (IOS) proposes to integrate its highly sensitive multi-agent chemical and toxic chemical detection sensor substrates, for mounting onto a quadcopter camera to assist in identifying/mapping target contaminants. This established optical sensor cladding technology developed at IOS adapts multiple componen ...

    SBIR Phase II 2018 Department of DefenseArmy
  6. Repurposed Software Programmable Radio Technology to Support Flexible Missile Uplink/Downlink Implementations

    SBC: Space Micro Inc.            Topic: A16078

    Space Micro's uLINK ("micro-LINK") SDR system is a robust missile data link radio inserted in existing Army hardware to satisfy the multi-mission demands of the IFPC-inc2 requirements. Based upon the robust DCT software defined radio, and interfacing existing RF and antennae hardware, we have shown that we can operate and is as a legacy data-link for initial integration, and as a tri-band (S, C, a ...

    SBIR Phase II 2018 Department of DefenseArmy
  7. Layer by Layer Multiple Antigen Nano-delivery Platform for Malaria Vaccine

    SBC: LUNA INNOVATIONS INCORPORATED            Topic: A16051

    Developing a safe and effective malaria vaccine remains the hope for reducing the spread and resurgence of the disease. In recent years, vaccine research has broadened with subunit protein, and DNA vaccines due to their inherent safety, simpler storage and easier production at the expense of attenuated and inactivated organism based approaches. RTS, S/AS01, the most advanced subunit vaccine, has u ...

    SBIR Phase II 2018 Department of DefenseArmy
  8. GR-TDM: A Framework for Design Space Exploration of Hardware Trojan Detection and Mitigation Tradeoffs

    SBC: GRAF RESEARCH CORPORATION            Topic: SB173004

    As integrated circuit dimensions shrink and U.S. fabrication facilities age, U.S. ASIC developers are increasingly turning to overseas foundries for the latest process nodes in device fabrication.This migration is especially impactful for DoD designers as critical military technology needs to be trusted and offshore fabrication has the potential to expose chips to malice during manufacture.Sensiti ...

    SBIR Phase I 2018 Department of DefenseDefense Advanced Research Projects Agency
  9. Data-Parallel Analytics on Graphics Processing Units (GPUs)

    SBC: Royal Caliber            Topic: ST13B004

    We are proposing to enable automated discovery of machine learning pipelines on graphs using our system of accelerated primitives. While our existing technology greatly reduces the need for users to understand super-computing, it still requires expertis...

    SBIR Phase II 2018 Department of DefenseDefense Advanced Research Projects Agency
  10. Distributed, Large Scale Spectrum Measurement and Analysis

    SBC: SHARED SPECTRUM COMPANY            Topic: SB162011

    Shared Spectrum Company (SSC), Intelligent Software Solutions (ISS), and the University of Tennessee at Chattanooga (UTC) propose to develop and demonstrate an innovative method for a large number (~50) of low altitude UAV to obtain information on spectrum use and activities. Our approach has multiple innovations: (1) ISS’s Seer, a “fuzzy” multi-hypothesis abductive reasoning system that pro ...

    SBIR Phase II 2018 Department of DefenseDefense Advanced Research Projects Agency
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