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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. Anisotropic Property Manipulation of Selective Laser Melted GRCop-84

    SBC: SPECIAL AEROSPACE SERVICES            Topic: AF18AT009

    In partnership with the Colorado School of Mines Alliance for the Development of Additive Processing Technologies and with support from the Johns Hopkins University Energetic Research Group, Special Aerospace Services will provide the Air Force with characterization of fully dense Selective Laser Melted GRCop-84 subjected to a variety of manipulations that affect key performance metrics for regene ...

    STTR Phase I 2018 Department of DefenseAir Force
  2. Complex Object Reflectance Characterization System (CORCS)

    SBC: NUTRONICS, INC.            Topic: AF18AT007

    Nutronics, Inc. and Montana State University propose to develop a method for characterization of the full Mueller matrix for reflective scattering from a test object. The Complex Object Reflectance Characterization System (CORCS) will initially be designed for laboratory use and characterization of test objects by active imaging to measure both the Mueller Matrix and the target depth associated wi ...

    STTR Phase I 2018 Department of DefenseAir Force
  3. Volumetric Wavefront Sensing for the Characterization of Distributed-Volume Aberrations

    SBC: Guidestar Optical Systems, Inc.            Topic: AF18AT006

    Modern Directed Energy (DE) missions require target engagements at low elevation angles and long ranges.These engagement geometries require propagation through distributed-volume turbulence. To correct for distributed-volume turbulence effects, an estimation of the turbulence along the propagation path is required. Correcting for these image aberrations will improve the quality of the target image ...

    STTR Phase I 2018 Department of DefenseAir Force
  4. Miniaturized Optical WDM Transmitter/Transceiver

    SBC: FREEDOM PHOTONICS LLC            Topic: AF18AT010

    The objective of this program is to develop, demonstrate and implement a low reconfigurable, reliable Free Space Optical (FSO) link supporting high bandwidth communications for satellite to satellite or satellite to ground communication. The FSO Transceiver (Transmitter/Receiver) to be implemented will be small Size, Weight, Power and Cost (SWaP-C) such that it can be easily carried by compact spa ...

    STTR Phase I 2018 Department of DefenseAir Force
  5. Detection of Radio Frequency and Magnetic Field Bioeffects in Living Cells

    SBC: QUINC.TECH INC.            Topic: AF18AT001

    The Biomagnetics Micro Dosimetry System (BMDS) program will design, model, and simulate a microdosimetry system that can measure and create a three dimensional map of weak radiofrequency signals in biological organisms. The heart of the BMDS project is the front end called a Quinc, that delivers very sensitive, broad band measurements with high spatial resolution.The Quinc based front end is a val ...

    STTR Phase I 2018 Department of DefenseAir Force
  6. AgileBeam Reconfigurable Free Space Optical Communication System

    SBC: SA PHOTONICS, LLC            Topic: AF18AT010

    Free Space Optical (FSO) communication systems provide many benefits for satellite communications, including high data rates and low Size, Weight and Power (SWaP) compared to traditional RF communication systems.Additionally, FSO systems operate without RF emissions and are inherently immune to RF interference and jamming.The narrow optical beams and small Field-of-View of the optical receivers al ...

    STTR Phase I 2018 Department of DefenseAir Force
  7. Non-Linear Adaptive Optics (NLAO)

    SBC: NUTRONICS, INC.            Topic: AF18AT008

    Nutronics, Inc. and Montana State University propose to develop an approach for non-linear control of hysteresis and incorporate (if necessary) integrated Multi-Input-Multi-Output real time control with this capability.Our control systems already include a proven high speed real time control approach to determine the optimal set of actuator commands that satisfy inter-actuator stroke limitations.O ...

    STTR Phase I 2018 Department of DefenseAir Force
  8. Stable High Bandwidth AO Control with physical DM constraints

    SBC: Guidestar Optical Systems, Inc.            Topic: AF18AT008

    Adaptive optics (AO) system performance is hindered by the mechanical limits of the deformable mirror (DM), namely stroke limits, interactuator stroke limits, and mechanical resonance.The nature of the multi-in multi-out (MIMO) control system does not lend itself well to notch filters to combat the mechanical resonances, and the stroke limits introduce non-linearities to the system.The traditional ...

    STTR Phase I 2018 Department of DefenseAir Force
  9. Complex Networks for Computational Urban Resilience (CONCUR)

    SBC: Perceptronics Solutions, Inc.            Topic: ST17C003

    CONCUR develops a computational framework for assessing and characterizing urban environments stability or fragility in response to volatility and stress, identifying specific weaknesses as well as key tipping points which could lead to rapid systemic failure. CONCUR explicitly models urban environments as emergent complex systems, focusing attention on the critical triggers that could lead to rap ...

    STTR Phase I 2018 Department of DefenseDefense Advanced Research Projects Agency
  10. Hybrid DNN-based Transfer Learning and CNN-based Supervised Learning for Object Recognition in Multi-modal Infrared Imagery

    SBC: TOYON RESEARCH CORPORATION            Topic: 1

    On this effort Toyon Research Corp. and The Pennsylvania State University are developing deep learning-based algorithms for object recognition and new class discovery in look-down infrared (IR) imagery. Our approach involves the development of a hybrid classifier that exploits both transfer learning and semi-supervised paradigms in order to maintain good generalization accuracy, especially when li ...

    STTR Phase I 2018 Department of DefenseNational Geospatial-Intelligence Agency
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