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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. Network Enabled Medical Training (NetEMT) Toolkit

    SBC: Quantified Design Solutions, LLC            Topic: A17101

    Many injuries in the battlefield are being treated by non-medical personnel(e.g. 42% of tourniquet applications are applied by non-medical personnel). Unfortunately, most non-medical personnel are not provided with opportunities to practice medical skills in a high stress environment prior to completing them during live missions. This lack of practice of critical skills is related to a need to foc ...

    SBIR Phase I 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. Scalable Dynamic GPS Broadband Patch Antenna Array

    SBC: Physical Optics Corporation            Topic: A16096

    To address the Armys need for an indoor GPS satellite constellation antenna array, Physical Optics Corporation (POC) proposes to develop a new Scalable Dynamic GPS Broadband Patch Antenna Array (SPAN) system. The proposed array is based on the novel integration of the broadband GPS-band smart antenna arrays coupled with EMI-immune fiber-optic interface between SPANs unique orbit-like platform loca ...

    SBIR Phase I 2018 Department of DefenseArmy
  6. Dynamic Pavement Deflection Measurement System for Roads and Airfields

    SBC: SA PHOTONICS, LLC            Topic: A17061

    The SA Photonics SafeLanding system offers a means for carrying out falling weight deflectometry measurement much more quickly than is possible with conventional equipment. With high-rate calibrated impact stimulation and all-optical sensing, SafeLanding collects high-quality deflectometry data while the unit is in motion. Unlike rolling wheel deflectometers, SafeLanding does not rely on heavy wei ...

    SBIR Phase I 2018 Department of DefenseArmy
  7. Android Biometric Authentication and Casualty Identification

    SBC: Physical Optics Corporation            Topic: A17065

    To address the Army need for biometric authentication and access management for medics and casualty identification on Android platforms, Physical Optics Corporation (POC) proposes to develop a new Android Biometric Authentication and Casualty Identification (ABACI) tool integrating a modular Android software toolset capable of dynamically utilizing one or more sensors for medic authentication and ...

    SBIR Phase I 2018 Department of DefenseArmy
  8. Smart Parachute Suspension Line

    SBC: Physical Optics Corporation            Topic: A17076

    To address the Army need for a low profile strain measurement system for parachute suspension lines, Physical Optics Corporation (POC) proposes to develop a new Smart Parachute Suspension Line (SPASL). It is based on novel construction of suspension and control cords using core-conducting bi-component fiber yarns in a double braid rope configuration. Specifically, the innovation in utilizing low a ...

    SBIR Phase I 2018 Department of DefenseArmy
  9. Reconfigurable, Hybrid, Three-dimensional Memory with Infinitely Scalable Interconnect Architecture (RHyTHM)

    SBC: Irvine Sensors Corporation            Topic: A17083

    Realizing that not only flash density but interconnectivity presents a challenge to implementing very-large memory arrays, Irvine Sensors Corporation proposes a Reconfigurable, Hybrid, Three-dimensional Memory (RHyTHM) with Infinitely Scalable Interconnect Architecture (ISIA).RHyTHM is a hybrid structure consisting of multiple consumer, off-the-shelf, stacked flash components, coupled with a custo ...

    SBIR Phase I 2018 Department of DefenseArmy
  10. Cluster UAS Smart Munition for Missile Deployment

    SBC: Technology Catalyst LLC            Topic: A17095

    Commercially available quad-copters could provide an innovative smart attack capability to existing military deployment platforms. This proposal demonstrates a plan to develop a payload for the ATACMS or GMLRS missile systems to deploy a "section" of UAS devices on the battlefield. Once there, these quad-copter UAS devices will navigate to and attack a target of interest using explosively formed p ...

    SBIR Phase I 2018 Department of DefenseArmy
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