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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. NDT of Fracture Toughness for Pipeline Steels

    SBC: FBS INC            Topic: 180PH1

    NDT of Fracture Toughness for Pipeline Steels3/16/2018Ultrasound-based technology to nondestructively determine fracture toughness of pipeline steels will be developed. Fracture toughness is the material parameter that, along with applied loading and flaw geometry, dictates the critical crack size, and therefore controls the flaw size that must be detected during inspections. A major challenge fac ...

    SBIR Phase II 2023 Department of Transportation
  2. Miniaturized End Effectors

    SBC: COMPASS SYSTEMS, INC.            Topic: N204A01

    Compass systems Inc. and its team possess the intellectual knowledge base and have sufficient expertise in robotic systems to develop miniaturized end effectors capable of performing maintenance and inspection operations. Our principal investigator has direct knowledge and experience in naval aviation maintenance processes through his past work experience at a fleet readiness center. By leveraging ...

    SBIR Phase II 2023 Department of DefenseNavy
  3. Acoustic Vector Sensors that Achieve Affordable Array Directivity

    SBC: QORTEK INC            Topic: N221070

    As anti-submarine warfare (ASW) technologies expanded rapidly during the Cold War, towed array systems such as Surveillance Towed Array Sonar System (SURTASS) were deployed with outstanding success at detecting submarines. Later TB-29(A) and TB-34 along with the Multi-Function Towed Array (MFTA) have further increased detection capabilities. This proposal aims to reduce the cost of vector sensor i ...

    SBIR Phase II 2023 Department of DefenseNavy
  4. Room-Temperature Filler for Honeycomb Repairs- MSC P4769

    SBC: MATERIALS SCIENCES LLC            Topic: N221006

    With the increased reliance on enhanced composite material system capabilities to meet the operational demands of the 21st century warfighter, there is a need to improve upon legacy repair and maintenance methods in order to maximize the life of these high-performance composite components and structures.  Under this SBIR program, the Navy is seeking novel, light-weight, fast-curing filler materia ...

    SBIR Phase II 2023 Department of DefenseNavy
  5. A Digital Twin Model for Robust 3D Woven PMC Pi Joints

    SBC: MATERIALS RESEARCH & DESIGN INC            Topic: N221067

    There is an increasing use of organic matrix composites in the airframes of many modern aircraft, including the F-15, F-16 and F-22. These materials are being integrated to achieve weight savings as well as additional fatigue resistance and strength. Recent advancements in Vacuum Assisted Resin Transfer Molding (VARTM) have further expanded the benefits offered by these materials by providing a lo ...

    SBIR Phase II 2023 Department of DefenseNavy
  6. Autonomous and Intelligent Aircraft Maintenance Technologies

    SBC: COMPASS SYSTEMS, INC.            Topic: N201015

    Today, autonomous and artificial intelligent (AI) systems are increasing the ability of both military and commercial systems to adapt and overcome the myriad of current and emerging global challenges. Expanded tasking includes the integration of autonomous and Artificial Intelligence (AI) sensors for manned and unmanned vehicles further expanding our capabilities and information gathering bandwidt ...

    SBIR Phase II 2022 Department of DefenseNavy
  7. Minimization of In-Band Interferers on Airborne Anti-Submarine System Perfromance

    SBC: RDA INC.            Topic: N182116

    Airborne ASW systems and sonobuoys operate in selected portions of the acoustic spectrum. Passive and active sensors not only contend with friendly forces operating in-band but must contend with other non-cooperative signals that degrade sensor performance including environmental interference, unintended out of band transmissions from our own sensors, and commercial interference from other sources ...

    SBIR Phase II 2021 Department of DefenseNavy
  8. Intelligent Tactical Assistant for Active SONAR (ITAAS)

    SBC: DANIEL H WAGNER ASSOCIATES INC            Topic: N211073

    Modern active sonar systems leverage numerous software tools to detect, classify, and track submarine threats. These tools include advanced signal processing algorithms, automated data association and tracking algorithms, contact classification algorithms, and tactical decision aids (TDAs) which attempt to recommend best practices to the user based upon the overall tactical picture. Ultimately, th ...

    SBIR Phase II 2023 Department of DefenseNavy
  9. Advanced Low Probability of Intercept/Low Probability of Detection (LPI/LPD) Radar Using Artificial Intellegence Driven Methods

    SBC: LAMBDA SCIENCE, INC.            Topic: N212114

    The Phase 1 effort successfully demonstrated that advanced LPI/LPD waveforms can be detected and classified with AI driven methods.  The overall findings have clearly defined the research direction of the Phase 2 effort.  Concentration on the combined selection of the waveform representation, and robust and compact discriminant selection with realistic radar waveform code length modulations wi ...

    SBIR Phase II 2023 Department of DefenseNavy
  10. Surveillance for Harbors using Intelligent Entities and Likelihood Distributions (SHIELD)

    SBC: TDI NOVUS INC            Topic: N112159

    SHIELD uses a combination of AIS, radar, and camera data to perform vessel classification and anomalous traffic identification in the maritime domain. By leveraging machine learning algorithms, the system extracts important features from the data, such as vessel speed, direction, and size, and uses these features to classify and identify vessels. Furthermore, the system can also detect anomalous t ...

    SBIR Phase II 2023 Department of DefenseNavy
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