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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. Multi-hop processing for OTHR range extension

    SBC: Decibel Research, Inc.            Topic: NGA191011

    The development of sophisticated anti-access/area denial (A2/AD) capabilities by our adversaries requires us to develop long range capabilities to mitigate this A2/AD threat. Extending the range of Over The Horizon Radars beyond their conventional single hop operating mode will potentially provide coverage out to 10000 km and beyond. We propose combining existing state-of-the art HF radar ray prop ...

    SBIR Phase I 2019 Department of DefenseNational Geospatial-Intelligence Agency
  2. Enhanced Canine Performance, Protection and Survivability

    SBC: Metro International Biotech, LLC            Topic: SOCOM172002

    Given the benefits of exercise on general health, orally active compounds that can mimic or potentiate the effects of exercise have been of keen interest as therapeutic and dietary ingredients. Our proposed approach for enhancement of USSOCOM Multi-Purpose Canine (MPC) endurance and sensory performance using an exercise mimetic is based on the observation that age-related decline of nicotinamide ...

    SBIR Phase I 2018 Department of DefenseSpecial Operations Command
  3. Group 2 (<55lbs) Unmanned Aerial System for Special Operations Forces Tactical-Level Intelligence, Surveillance, and Reconnaissance Operations

    SBC: Sealandaire Technologies, Inc.            Topic: SOCOM172005

    SeaLandAire Technologies, Inc. (SLA) proposes to meet this Group 2 need with an electric drive concept that will be capable of a 20-30 lbs. modular payload, with comparable range and endurance to current grp 2 ISR UAS, while still maintaining sufficient ISR capabilities. This UAS concept is able to covertly and safely deliver payload to within 1 meter accuracy, then extract a different payload an ...

    SBIR Phase I 2018 Department of DefenseSpecial Operations Command
  4. Group 2 (<55lbs) Unmanned Aerial System for Special Operations Forces Tactical-Level Intelligence, Surveillance, and Reconnaissance Operations

    SBC: Knight Technical Solutions, LLC            Topic: SOCOM172005

    The proposed Group 2 UAS is a long endurance fixed wing aircraft, a secure communications system and a portable ground station. The light weight aircraft features a high aspect ratio wing and is powered by an electric ducted fan for maximum efficiency. The modular aircraft system is one man portable and designed to be packed out on a molle backpack configuration. The conceptual airframe design ...

    SBIR Phase I 2018 Department of DefenseSpecial Operations Command
  5. SUAS Killer, Identifier, and Tracker

    SBC: Physical Optics Corporation            Topic: SOCOM173005

    To address USSOCOMs need for a system to detect, locate, track, and either disable and/or destroy a small unmanned aerial system (SUAS) from a distance, Physical Optics Corporation (POC) proposes to develop the new SUAS Killer, Identifier, and Tracker (SKEET) system. The SKEET system is based on a new design that combines state-of-the-art airspace monitoring technology utilizing compact scanning r ...

    SBIR Phase I 2018 Department of DefenseSpecial Operations Command
  6. Low-Shot Detection in Remote Sensing Imagery

    SBC: TOYON RESEARCH CORPORATION            Topic: NGA172002

    Toyon Research Corporation proposes to research and develop algorithms for low-shot object detection, adapting popular techniques to address the complexities inherent in ATR for remote sensing. Traditional object detection algorithms rely on large corpora of data which may not be available for more exotic targets (such as foreign military assets), and therefore, traditional Convolutional Neural Ne ...

    SBIR Phase I 2018 Department of DefenseNational Geospatial-Intelligence Agency
  7. Blending Ground View and Overhead Models

    SBC: Arete Associates            Topic: NGA181008

    We propose to build ARGON, the ARet Ground-to-Overhead Network. The network will ingest analyst-supplied ground-level imagery ofobjects and retrieve instances of those objects in overhead collections, providing tips back to the analysts. A proprietary method of trainingthe network, leveraging in-house capabilities, data sources, and tools, will be critical to its success. During Phase I, we will p ...

    SBIR Phase I 2018 Department of DefenseNational Geospatial-Intelligence Agency
  8. Improving Uncertainty Estimation with Neural Graphical Models

    SBC: MAYACHITRA, INC.            Topic: NGA181005

    Building interpretable, composable autonomous systems requires consideration of uncertainties in the decisions and detections theygenerate. Human analysts need accurate absolute measures of probability to determine how to interpret and use the sometimes noisy resultsof machine learning systems; and composable autonomous systems need to be able to propagate uncertainties so that later reasoningsyst ...

    SBIR Phase I 2018 Department of DefenseNational Geospatial-Intelligence Agency
  9. Low-Shot Detection in Remote Sensing Imagery

    SBC: TOYON RESEARCH CORPORATION            Topic: NGA181010

    The National Geospatial-Intelligence Agency (NGA) ingests and analyzes raw imagery from multiple sources to form actionable intelligenceproducts that can be disseminated across the intelligence community (IC). To effectively meet these demands NGA must continue to improveits automated and semi-automated methods for target detection and classification. Of particular concern is furthering NGA's abil ...

    SBIR Phase I 2018 Department of DefenseNational Geospatial-Intelligence Agency
  10. Automated Assessment of Urban Environment Degradation for Disaster Relief andReconstruction

    SBC: TOYON RESEARCH CORPORATION            Topic: NGA181004

    Toyon Research Corp. proposes development of a system that automates disaster assessment based on fusion of overhead and ground-basedimages, video, and other data. In Phase I, we will investigate various possible data sources and the benefits of fusing the data in automatedanalysis. We will select and curate data for processing in a Phase I feasibility study. Damage assessment will be performed in ...

    SBIR Phase I 2018 Department of DefenseNational Geospatial-Intelligence Agency
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