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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. Ceramic Matrix Composite Fins and Nosetips for Gun-Launched Projectiles

    SBC: ULTRAMET            Topic: SCO182003

    Boeing Defense Systems is developing a guided hypervelocity projectile (HVP) and associated integrated launch package assembly. The nosetip and fixed and rotating fin components present particular challenges due to the high aeroheating and dynamic pressure loads and associated temperatures, thermal shock, and oxidizing conditions. Low drag requires sharp tip and edge features on the nose and fins, ...

    SBIR Phase I 2019 Department of DefenseOffice of the Secretary of Defense
  2. Maritime Target Classification from Inverse Synthetic Aperture Radar (ISAR) Using Machine Learning/Toyon Research Corp.

    SBC: TOYON RESEARCH CORPORATION            Topic: SCO182008

    Toyon Research Corp. proposes to develop innovative algorithms to perform automatic target detection (ATR), localization, classification, and sub-classification of maritime targets in ISAR imagery. The proposed algorithms are based on a careful analysis of reflection-mode ISAR imaging systems that aims to address complications that are unique to the images produced in this modality, such as poor r ...

    SBIR Phase I 2019 Department of DefenseOffice of the Secretary of Defense
  3. Maritime Target Classification from Inverse Synthetic Aperture Radar (ISAR) Using Machine Learning/Electromagnetic Systems, Inc.

    SBC: ELECTROMAGNETIC SYSTEMS, INC.            Topic: SCO182008

    EMSI proposes to demonstrate the feasibility of extending our machine-learning-based SAR classifiers to provide real-time high confidence maritime target classification from ISAR data collected and processed onboard airborne ISR platforms. To this end, we will modify our classifier architectures to accommodate target motion and ISR platform constraints, simulate realistic ISAR data sets, and deter ...

    SBIR Phase I 2019 Department of DefenseOffice of the Secretary of Defense
  4. Fully Encrypted Neural Network Training & Inference

    SBC: INTELLISENSE SYSTEMS INC            Topic: SCO182009

    To address the SCO’s need for secure computing with neural networks, Intellisense Systems, Inc. (ISI) proposes to develop a new Fully Encrypted Neural Network Training & Inference (FENNTI) framework. It is based on a novel use of homomorphic encryption (HE) for both neural network inference and training. The method works by first modifying existing arbitrary neural network architectures to ...

    SBIR Phase I 2019 Department of DefenseOffice of the Secretary of Defense
  5. High-Dynamic Target Tracking in Multisensor Environments

    SBC: NUMERICA CORPORATION            Topic: SCO182005

    The Strategic Capabilities Office (SCO) of OSD is leading a program to demonstrate a Hyper Velocity Projectile (HVP) Gun Weapon System (HGWS) within the DoD. Emerging missile threats are highly agile, exhibit unpredictable behavior and are often protected by sophisticated counter-measures. To support the deployment of HVP weapon systems for defense against these threats, a comprehensive multi-targ ...

    SBIR Phase I 2019 Department of DefenseOffice of the Secretary of Defense
  6. Multi-Sensor Fire Control System for Tracking Highly Maneuverable Targets

    SBC: VENATOR SOLUTIONS, LLC            Topic: SCO182005

    Recent advances in aeronautical design and development has contributed to a significant increase in the vulnerability of the warfighter’s land and sea-based assets from threat-targets exhibiting unpredictable, high-dynamic motion, evasive control, and countermeasure usage. The primary defensive strategy against these targets is a fire control radar system. These systems typically use a sing ...

    SBIR Phase I 2019 Department of DefenseOffice of the Secretary of Defense
  7. High Acceleration and Hypervelocity Radiofrequency Communications and Sensing

    SBC: FIRST RF CORPORATION            Topic: SCO182004

    In gun-launched projectile applications, the launch accelerations are harsh and can be up to 50,000 g. In order to enable capability to operate in both high shock and aerothermal conditions, FIRST RF has developed compatible antenna technology. Prototypes of these sensors have been fabricated and validated to similar shock and thermal conditions. Additionally, as with all small weapons, space is v ...

    SBIR Phase I 2019 Department of DefenseOffice of the Secretary of Defense
  8. Maritime Target Classification from Inverse Synthetic Aperture Radar (ISAR) Using Machine Learning/Arete Associates

    SBC: Arete Associates            Topic: SCO182008

    The Strategic Capabilities Office of OSD is seeking to use machine learning to produce a robust classification capability using ISAR for a relevant radar sensor system. Areté Associates proposes an advanced machine learning approach to perform robust classification with a path towards real-time classification performance. The proposed approach employs a robust method to generate a valid, balanc ...

    SBIR Phase I 2019 Department of DefenseOffice of the Secretary of Defense
  9. High-Throughput Computer Vision/Etegent Technologies, LTD

    SBC: ETEGENT TECHNOLOGIES, LTD.            Topic: SCO182007

    Etegent is proposing an agile hardware platform to enable object detection at extremely high pixel per watt rates and is also capable of quickly incorporating new algorithmic approaches. The core enabling technology of this system is a multicore system on a chip (SoC) server utilizing several low-power COTS processors configured with a high-speed interconnect switch. Etegent has developed a variet ...

    SBIR Phase I 2019 Department of DefenseOffice of the Secretary of Defense
  10. Naval ISAR Target Recognition (NITRO)/Stottler Henke Associates, Inc.

    SBC: STOTTLER HENKE ASSOCIATES, INC            Topic: SCO182008

    Stottler Henke proposes the Naval ISAR Target RecOgnition (NITRO) system, leveraging our related past work in ship classification from ISAR imagery. NITRO will be able to maintain low space, weight, and power (SWaP) constraints by utilizing recent advancements in mobile processors, such as AMD’s APU chips (a single chip CPU-GPU hybrid) or Intel’s CPU-FPGA hybrid chips. NITRO will inc ...

    SBIR Phase I 2019 Department of DefenseOffice of the Secretary of Defense
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