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Award Data
The Award database is continually updated throughout the year. As a result, data for FY23 is not expected to be complete until September, 2024.
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.
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Unified sensor for atmospheric turbulence and refractivity characterization
SBC: G. A. Tyler Associates, Inc. Topic: AF17AT008In this effort, tOSC and the University of New Mexico COSMIAC (Configurable Space Microsystems Innovation Applications Center) will combine to generate a Target-in-the-Loop (TIL) system concept that can simultaneously measure the strength of atmospheric turbulence and scintillation, as well as the refractivity occurring at the measurement time. For this system concept, we will leverage existing tO ...
STTR Phase II 2019 Department of DefenseAir Force -
Unified sensor for atmospheric turbulence and refractivity characterization
SBC: MZA ASSOCIATES CORP Topic: AF17AT008MZA partnered with the Michigan Technological University (MTU) proposes development and testing of key components for our unified Atmospheric Refractivity and Turbulence Sensor (ARTS.) Software upgrades will be made to MZA’s DELTA-Sky sensor to enable atmospheric refraction measurements in addition to existing turbulence profiling. The illuminator assembly to implement the ARTS probe laser ...
STTR Phase II 2019 Department of DefenseAir Force -
Verification and Validation of Algorithms for Resilient Complex Software Controlled Systems
SBC: XL SCIENTIFIC LLC Topic: AF17CT05This effort seeks verification tools and techniques to ensure safety and stability of spacecraft Guidance, Navigation, and Control (GN&C) algorithms, particularly the attitude control system integrated with autonomy software. Advanced control algorithms and autonomy are increasingly necessary to enable responsiveness of fleets of vehicles to attitude constraints and object avoidance. Verus Researc ...
STTR Phase II 2019 Department of DefenseAir Force -
Vibration imaging for the characterization of extended, non-cooperative targets
SBC: Guidestar Optical Systems, Inc. Topic: AF19AT006Locating objects that vibrate is a way to discern potential threats and locate targets. However, current vibrometry technology typically measures only the global vibration of target and cannot create an extended spatial measurement of the vibration profile of the target. These solutions cannot identify what the target is, nor can they locate potential weak spots on the target, because they lack sp ...
STTR Phase I 2019 Department of DefenseAir Force -
Vibration imaging for the characterization of extended, non-cooperative targets
SBC: TAU TECHNOLOGIES LLC Topic: AF19AT006Tau Technologies is teaming with Dr. David Voelz and his research group at New Mexico State University (NMSU) to propose “Vibration Imaging for the characterization of extended non-cooperative targets�, which employs dual-pulses in two different variations for vibration imaging in order to characterize non-cooperative targets at extended standoffs. One method is based on double-pulse ...
STTR Phase I 2019 Department of DefenseAir Force -
Virtual Reality for Multi-INT Deep Learning (VR-MDL)
SBC: Information Systems Laboratories, Inc. Topic: AF19AT010Recent advances and successes of deep learning neural networks (DLNN) techniques and architectures have been well publicized over the last several years. Voluminous, high-quality and annotated training data, or trial and error in a realistic environment, is required to achieve the promised performance potential of DLNNs. Unfortunately for DoD and/or Intelligence Community (IC) applications of mult ...
STTR Phase I 2019 Department of DefenseAir Force -
VLSI CMOS Memristor Building Blocks for Future Neuromorphic Processors
SBC: NUGENT, MICHAEL ALEXANDER Topic: F10BT31024ABSTRACT:Both civilian and military personnel live in a world awash in information while our military commands reconnaissance and weapons platforms of all shapes and sizes over a global and increasingly congested theater. We need new technology to help us sort, prioritize, make sense, and act on the growing streams of information.In Phase 1 we have proven feasible a core CMOS+Memristor circuit cap ...
STTR Phase II 2013 Department of DefenseAir Force -
VLSI Compatible Silicon-on-Insulator Plasmonic Components
SBC: ITN ENERGY SYSTEMS, INC. Topic: AF08BT18This Small Business Technology Transfer Phase I project will develop ultradense, low-power plasmonic integration components and devices for on-chip manipulation and processing of optical signals. Both passive and active components will be studied. Detailed performance predictions will be obtained through finite element modeling (FEM) of the harmonic Maxwell’s equations. The FEM provides detai ...
STTR Phase I 2010 Department of DefenseAir Force -
Volume Digital Holographic Wavefront Sensor Phase 2
SBC: NUTRONICS, INC. Topic: AF18AT006Through the execution of our Phase 1 effort, Nutronics, Inc. and Montana State University developed an improved means to optimize the Pellizzarri cost functional for coherent imaging using digital holography. Our algorithm developed during the Phase 1 effort accelerates convergence times by a factor of 20-40 for the majority of scenarios evaluated. Our proposed Phase 2 effort has a two-fold focus: ...
STTR Phase II 2019 Department of DefenseAir Force -
Wave-Optic Propagation Computation Enabled by Machine Learning Algorithms (WOPA)
SBC: Luminit LLC Topic: AF18BT004To address the U.S. Air Force need for Developing innovative wave-optics Propagation methods to model laser systems that are faster, efficient and more accurate, Luminit, LLC, and University of Southern California (USC) propose to develop Wave-Optic Propagation Computation Enabled by Machine Learning Algorithms (WOPA). The proposed algorithms will be based on cutting off redundant frequencies upon ...
STTR Phase I 2019 Department of DefenseAir Force