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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. Fuel Efficient Nanofluid Gear Oil

    SBC: Pixelligent Technologies, LLC            Topic: A15AT018

    Improving vehicle fuel efficiency for the military can significantly reduce costs and reduce risk to solider safety. One way to improve vehicle efficiency for new and legacy vehicles is to reduce frictional loses in the drivetrain through use of lower viscosity lubricants. However, this comes with the risk of reducing durability of drivetrain components through increased wear, pitting and scuffing ...

    STTR Phase II 2018 Department of DefenseArmy
  2. A Platform Agnostic Low SWaP-C Chirped LFMCW Radar for counter-UAS application

    SBC: INTELLIGENT FUSION TECHNOLOGY, INC.            Topic: A17126

    This proposal presents A Platform Agnostic Low SWaP-C Chirped LFMCW Radar for counter-UAS application. The radar utilizes IFT’s unique gated radar structure to reduce transmission carrier leakage into the receiver channel and minimize the oscillator phase noise influence on the target signal. In addition, the digital signal processing provides high processing gain. These enable the radar to achi ...

    SBIR Phase I 2018 Department of DefenseArmy
  3. Software Based All Digital Wireless Modem

    SBC: FAST FIT TECHNOLOGIES LLC            Topic: A16113

    The research conducted on the all software digital COTS modem provides a new paradigm in the creation, manipulation, and processing of communication waveforms that removes the dependency on "purpose built" modem hardware for satellite, terrestrial, and airborne communications. The flexibility and adaptability of this new paradigm will result in an architecture to breath new life into old/antiquate ...

    SBIR Phase II 2018 Department of DefenseArmy
  4. A Novel, Nanostructured, Metal-organic Frameworks-Based Product Loss Prevention Technology in the Oil and Natural Gas Sector

    SBC: FRAMERGY INC            Topic: 17NCER2C

    To reach the end user, oil and gas production at the wellhead must be transmitted through the country and distributed to a wide range of customers. This logistical system requires natural gas gathering lines, processing facilities, product storage tanks and lots of other equipment. What results is air pollution caused by industry losses during these operations and the use of continuous or intermit ...

    SBIR Phase I 2018 Environmental Protection Agency
  5. Multiscale Fast and Distributed Data and Statistics Summarization

    SBC: Intelligent Automation, Inc.            Topic: A17AT010

    Over the last decade the amount of data available from the internet, sensors and other sources has grown dramatically providing the opportunity to gain novel insights in many fields. Uncovering non-linear low dimensional structure in high-dimensional data (i.e., manifold learning), a key to summarization, remains a challenging problem which ultimately inhibits knowledge discovery. Intelligent Auto ...

    STTR Phase II 2018 Department of DefenseArmy
  6. ORION: Operational Robot with Intelligent Off-road Navigation

    SBC: Intelligent Automation, Inc.            Topic: A17AT019

    For Robotic/Autonomous Systems (RAS) to be truly effective in the battlefield, they need to be integrated with intelligent decision-making capabilities. In particular, the following capabilities will help them dealing with the challenging real-world problems of off-road navigation: 1) Accurate terrain traversability assessment; 2) Optimal trajectory computation; and 3) Effective maneuver selection ...

    STTR Phase II 2018 Department of DefenseArmy
  7. Low-Shot Detection in Remote Sensing Imagery

    SBC: Next Century Corporation            Topic: NGA172002

    Next Century Corporation proposes the development of Muggsy, a low-shot deep learning detection prototype system that learns to recognize uncommon targets in remote imagery. Our Phase I research extends and leverages an image classification system of our own design called EvoDevo. EvoDevo evolves its own neural network architecture before training to meet the complexity of the data. Muggsy uses le ...

    SBIR Phase I 2018 Department of DefenseNational Geospatial-Intelligence Agency
  8. GFNet: Gnostic Fields based Low-Shot Learning for Target Detection in Remote Sensing

    SBC: Intelligent Automation, Inc.            Topic: NGA172002

    To detect uncommon targets in remote sensing imagery, it is quite often that very few prior examples are available. This so-called low-shot detection remains a very challenging problem in remote sensing, despite the recent development in state-of-the-art object detection algorithms such as Faster R-CNN and YOLO, and low-shot learning methods such as feature shrinking, model regression and memory a ...

    SBIR Phase I 2018 Department of DefenseNational Geospatial-Intelligence Agency
  9. DNC-GD: Deep Neural Network Compression for Geospatial Data

    SBC: Intelligent Automation, Inc.            Topic: NGA181009

    Following technology advances in high-performance computation systems and fast growth of data acquisition, a technical breakthroughnamed Deep Learning made remarkable success in many research areas and applications. Nevertheless, the progress of hardwaredevelopment still falls far behind the upscaling of deep neural network (DNN) models at the software level. NGA seeks to apply neuralnetwork minia ...

    SBIR Phase I 2018 Department of DefenseNational Geospatial-Intelligence Agency
  10. TOFENetTopographic Features Extraction Network

    SBC: Intelligent Automation, Inc.            Topic: NGA181001

    Topographic features found in ground-based natural images contain information that is useful for a variety of applications including locationestimation and navigation. Traditionally these features have been manually labeled by analysts which is costly and time consuming, especiallyconsidering the volume of readily available data. We propose a novel method for extracting topographic features from s ...

    SBIR Phase I 2018 Department of DefenseNational Geospatial-Intelligence Agency
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