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The Award database is continually updated throughout the year. As a result, data for FY21 is not expected to be complete until September, 2022.

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. Marburg Virus Prophylactic Medical Countermeasure

    SBC: Flow Pharma, Inc.            Topic: CBD18A002

    Through this STTR contract, we propose to evaluate the efficacy of our vaccine, FlowVax Marburg, in nonhuman primates (NHPs). This will be achieved through four Tasks. In Task 1, we will manufacture the vaccine in a quantity sufficient for the animal studies. In Task 2, we will perform MHC genotyping on a representative population of NHPs and, based on results, select a set of MHC-matched NHPs for ...

    STTR Phase II 2020 Department of DefenseOffice for Chemical and Biological Defense
  2. Marburg Virus Prophylactic Medical Countermeasure

    SBC: MAPP BIOPHARMACEUTICAL, INC.            Topic: CBD18A002

    There are currently no vaccines or therapeutics available for Marburg Virus Disease (MVD). Given the specter of weaponization and the terrible morbidity and high mortality rate of MVD, this represents a critical threat to the operational readiness of the Warfighter. While traditional vaccines have contributed greatly to public health, they have some limitations especially in the context of operati ...

    STTR Phase II 2020 Department of DefenseOffice for Chemical and Biological Defense
  3. Fully Adaptive Radar Resource Allocation

    SBC: INFORMATION SYSTEMS LABORATORIES, INC.            Topic: AF19BT003

    In this proposal, ISL and MTRI will develop an advanced cognitive fully adaptive radar (CoFAR) and electronic warfare (EW) resource optimizer and scheduler. While the basic architecture for CoFAR has been developed previously, there is a need for a real-time scheduler that can handle the many complex operations and demands on sensor tasking that will arise when operating in a highly contested envi ...

    STTR Phase I 2020 Department of DefenseAir Force
  4. Passive Image Processing Algorithms for Automated Target Attitude Estimation

    SBC: TOYON RESEARCH CORPORATION            Topic: AF19BT005

    Weapons systems testing and analysis is crucial to engineering, understanding, qualifying, and deploying advanced weapons systems. With the boom in camera technology over the past decade image based methods to support weapons testing and analysis have become the state of practice for military test ranges. At the same time, there has been an explosion of research and development in computer vision ...

    STTR Phase I 2020 Department of DefenseAir Force
  5. Information Extraction for New Emerging Noisy User-generated Micro-Text

    SBC: INFERLINK CORPORATION            Topic: AF19BT006

    Neural networks have proved highly effective at extracting information from text. However, noisy microtext has proved to be particularly difficult because low-level syntactic cues much less useful. In this project, we propose to explore ways of incorporating strong semantic, expectation-based models into a neural net architecture to improve performance on microtext extraction. In phase I, we will ...

    STTR Phase I 2020 Department of DefenseAir Force
  6. Adaptable Cyber Defense for Autonomous Air Operations

    SBC: INFERLINK CORPORATION            Topic: AF19CT003

    Cyber defense is difficult, but presents a particularly thorny problem for legacy systems, including legacy embedded systems, where in many such cases source code may not even be available. In this project, we proposed to investigate and extend a pattern-based approach recently developed by USC-ISI for analyzing and retrofitting binary code to protect against potential attacks. In this project, we ...

    STTR Phase I 2020 Department of DefenseAir Force
  7. Transfer Learning and Deep Transfer Learning for Military Applications

    SBC: Arete Associates            Topic: AF19CT004

    Aided Target Recognition (AiTR) algorithms augment human decision-making, but require a large database of labeled targets for training. Applied to new domains, these algorithms fail to transfer knowledge and require substantial retraining. Areté and University of Alabama Huntsville (UAH) propose the development of the Domain Extracted Feature Transfer (DEFT) Network to transfer knowledge from a ...

    STTR Phase I 2020 Department of DefenseAir Force
  8. Dynamic Bias APD Receiver Array

    SBC: NU TREK INC            Topic: AF19CT006

    The program has two trusts: (1) Using dynamic biasing to address arbitrary pulse trains, such as would be present in LIDAR and other forms of EO/IR imaging and periodic pulse trains, such as in telecommunications; and (2) Developing an APD the meets program requirements such as a cutoff wavelength >1.6 m, low dark current, low excess noise and a >200 K operating temperature. In the proposed ...

    STTR Phase I 2020 Department of DefenseAir Force
  9. Fiber Optic Sensor System for Machinery Vibration Monitoring and Diagnosis

    SBC: Intelligent Fiber Optic Systems Corporation            Topic: AF19CT008

    IFOS proposes an approach to developing an optical fiber Bragg grating (FBG)-based real-time instrumentation system for machinery vibration monitoring and diagnosis. IFOS’ key innovation is in the use of an advanced fiber optic sensing system that can make temperature and vibration measurements, with vibration signature identification and statistics tracking techniques for the assessment of ...

    STTR Phase I 2020 Department of DefenseAir Force
  10. Super-High-Resolution, Distributed Photonic Sensors for Aerospace Platforms

    SBC: Intelligent Fiber Optic Systems Corporation            Topic: AF19CT010

    IFOS and STTR partner Stanford University propose an innovative fiber-optic sensor array leveraging the latest advances in slow-light fiber Bragg gratings (SL-FBG). SL-FBGs substantially improve upon the sensitivity of commercially proven conventional FBGs (C-FBG) by more than 3 orders of magnitude and can be interrogated at megahertz rates. SL-FBG differ from C-FBG in their refractive index modul ...

    STTR Phase I 2020 Department of DefenseAir Force
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