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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. Faster Optical Modem for Underwater Data Acquisition

    SBC: SA PHOTONICS, LLC            Topic: NGA182001

    SA Photonics’ Optical Navigation and Ranging (ONAR) system is an interrogative system that operate underwater in wavelength range of blue/green (450-540 nm) and enables navigational correction to IMU based dead reckoning navigation. The location based beacons are battery operated and have operational life span of over one year. The system is designed to operate in on demand burst mode so that no ...

    SBIR Phase I 2019 Department of DefenseNational Geospatial-Intelligence Agency
  2. Faster Optical Modem for Underwater Data Acquisition

    SBC: SONALYSTS INC            Topic: NGA182001

    To address NGA’s requirements, Sonalysts’ team of world-class experts in underwater optical communication proposes development and implementation of the Precision Optical Navigation Transceiver for Undersea Systems (PONTUS). PONTUS will transfer navigation information from an Underwater Navigation Beacon (UNB) to an Unmanned Undersea Vehicle (UUV) in an electromagnetic-spectrum-denied (e.g., G ...

    SBIR Phase I 2019 Department of DefenseNational Geospatial-Intelligence Agency
  3. A Multi-Branch Network for Automated VNIIRS Assessment of Motion Imagery

    SBC: TOYON RESEARCH CORPORATION            Topic: NGA191003

    Due to the lack of consistency in existing automated methods for assigning VNIIRS levels to motion imagery, and the overwhelming human resources required to manually assign levels, a new method of automated/semi-automated VNIIRS assessment is needed. In recent years, advancements in deep learning have provided solutions to previously intractable computer vision problems. In many cases, automated d ...

    SBIR Phase I 2019 Department of DefenseNational Geospatial-Intelligence Agency
  4. 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
  5. 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
  6. Handheld Hidden Chamber Detection

    SBC: TIALINX, INC.            Topic: SOCOM173004

    SOCOM requires rapid implementation and delivery of a handheld, automated hidden chamber sensor system to detect, locate, and discriminate hidden compartments. TiaLinxs Eagle-NC is a wall imager that operates as an ultra-wideband (UWB) radio frequency (RF) sensor integrated with advanced computer vision algorithms, state-of-the-art computer processor technologies, and has a fully integrated displa ...

    SBIR Phase I 2018 Department of DefenseSpecial Operations Command
  7. 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
  8. Human Performance Optimization: Ketone Esters for Optimization of Operator Performance in Hypoxia

    SBC: HVMN Inc.            Topic: SOCOM17C001

    In the setting of altitude-induced hypoxia, operator cognitive capacity degrades and can compromise both individual and team performance. This degradation is linked to falling brain energy (ATP) levels and an increased reliance on anaerobic energy production from glucose. Ketone bodies are the evolutionary alternative substrate to glucose for brain metabolic requirements; previous studies have sho ...

    STTR Phase I 2018 Department of DefenseSpecial Operations Command
  9. Hybrid DNN-based Transfer Learning and CNN-based Supervised Learning for Object Recognition in Multi-modal Infrared Imagery

    SBC: TOYON RESEARCH CORPORATION            Topic: 1

    On this effort Toyon Research Corp. and The Pennsylvania State University are developing deep learning-based algorithms for object recognition and new class discovery in look-down infrared (IR) imagery. Our approach involves the development of a hybrid classifier that exploits both transfer learning and semi-supervised paradigms in order to maintain good generalization accuracy, especially when li ...

    STTR Phase I 2018 Department of DefenseNational Geospatial-Intelligence Agency
  10. Algorithms for Look-down Infrared Target Exploitation

    SBC: SIGNATURE RESEARCH, INC.            Topic: 1

    Signature Research, Inc. (SGR) and Michigan Technological University (MTU) propose a Phase I STTR effort to develop a learning algorithm which exploits the spatio-spectral characteristics inherent within IR imagery and motion imagery.Our archive of modelled and labeled data sets will allow our team to thoroughly capture the variable elements that will drive machine learning performance.The overall ...

    STTR Phase I 2018 Department of DefenseNational Geospatial-Intelligence Agency
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