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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. Conformal Aerodynamic Controls for Supermaneuverable High-Speed Vehicles

    SBC: ATA Engineering, Inc.            Topic: MDA18T002

    High G Aerodynamic Controls | Approved for Public Release 18-MDA-9707 (3 Jul 18)

    STTR Phase I 2019 Department of DefenseMissile Defense Agency
  2. Low Toxicity, Non-cryogenic Liquid Propellant Upper Stage Engine

    SBC: Science and Technology Applications, LLC            Topic: MDA18T005

    Our vision for the next generation missile and space propulsion engine is a flexible and non-toxic propulsion technology using HAN/kerosene, offering variable thrust with a high degree of mission tailoring. Additionally, high bulk density of HAN/kerosene bi-propellant improves stage mass fraction and delivers performance metrics that exceed current toxic storable propellants. We propose an innovat ...

    STTR Phase I 2019 Department of DefenseMissile Defense Agency
  3. Storable Clean Ethane/ethylene Nitrous Engine (SCENE)

    SBC: PIONEER ASTRONAUTICS            Topic: MDA18T005

    he Storable Clean Ethane-ethylene Nitrous Engine (SCENE) is a proposed technology designed to provide upper stages and spacecraft with non-toxic, liquid, non-cryogenic, high-performance propulsion with an Isp on the order of 300 seconds. The propellant components are stored as liquids under their saturated vapor pressures. With the SCENE, nitrous oxide is used as an autogenously pressurized oxidiz ...

    STTR Phase I 2019 Department of DefenseMissile Defense Agency
  4. Uncertainty Reduction in High Speed Flight Vehicle Modeling

    SBC: M4 ENGINEERING, INC.            Topic: MDA18T006

    Uncertainty Reduction in High Speed Flight Vehicle Modeling | Approved for Public Release 18-MDA-9707 (3 Jul 18)

    STTR Phase I 2019 Department of DefenseMissile Defense Agency
  5. Advanced Command and Control Architectures for Autonomous Sensing

    SBC: TOYON RESEARCH CORPORATION            Topic: N18BT030

    We propose to develop an innovative open architecture for the semi-autonomous command and control (C2) of teaming Unmanned Aircraft Systems (UAS). The proposed architecture, based upon Toyon’s Decentralized Asset Management system, supports both centralized and decentralized fusion and control autonomy solutions as well as hybrids approaches. Leveraging STANAG-4586, TCP/IP, UPD, Google™ protob ...

    STTR Phase I 2019 Department of DefenseNavy
  6. Blending Classical Model-Based Target Classification and Identification Approaches with Data-Driven Artificial Intelligence

    SBC: TOYON RESEARCH CORPORATION            Topic: N18BT033

    Toyon Research Corp. and the University of California propose to develop innovative algorithms to perform automatic target recognition (ATR), localization, and classification of maritime and land targets in EO/IR, LiDAR, and SAR imagery. The proposed algorithms are based on recent developments made at the University of California, which outline a strong mathematical framework for naturally blendin ...

    STTR Phase I 2019 Department of DefenseNavy
  7. Optimized Higher Power Microwave Sources

    SBC: Epirus, Inc.            Topic: N19AT001

    Epirus presents a high powered microwave source that leverages ultra high power density solid state materials, called Leonidas, to meet all of the government’s objectives for the vehicle stop and vessel stop mission. The Leonidas unit has already achieved over 10 kW of effective radiated power (ERP) in laboratory tests using software definable solid state technology and we show how this scales t ...

    STTR Phase I 2019 Department of DefenseNavy
  8. Enhanced Sensor Resource Management Utilizing Bayesian Inference

    SBC: GCAS, Inc.            Topic: N19AT002

    This proposal describes the use of machine learning, data mining and Bayesian inference algorithms for incorporation into a surveillance aircraft cognitive radar system. The need for incorporation of higher-order uncertainty distributions will also be assessed. This will result in enhanced sensor resource management capability for surveillance aircraft radar.

    STTR Phase I 2019 Department of DefenseNavy
  9. Innovations in Designing Damage Tolerant Rotorcraft Components by Interface Tailoring

    SBC: HARP ENGINEERING LLC            Topic: N19AT003

    The performance of a composite material is heavily influenced by the strength and toughness of the interlaminar region, which is the resin rich area between the plies of a fiber reinforced composite. The interlaminar region generally provides a direct path for crack propagation since no continuous reinforcement is present and is often the cause of failure in materials subjected to cyclic loading s ...

    STTR Phase I 2019 Department of DefenseNavy
  10. Process to Mitigate Catastrophic Optical Damage to Quantum Cascade Lasers

    SBC: Irglare, LLC            Topic: N19AT004

    The development of a catastrophic optical damage model for quantum cascade lasers describing instantaneous laser damage at high optical power levels is proposed. The model will be validated by comparison to experimental data. Based on obtained results, changes to laser design and laser fabrication resulting in an increased damage threshold will be implemented. The work will ultimately result into ...

    STTR Phase I 2019 Department of DefenseNavy
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