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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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Shear Stabilization Based Framework for the Failure Testing and Analysis of HSCs
SBC: Roccor, LLC Topic: AF17AT019Over the past 2 years, Roccor has successfully qualified and delivered High Strain Composite (HSC) products for space-flight customers including, 1) RF-Furlable boom, 2) a furlable-antenna system; and is currently qualifying HSC products for space-flight customers including 3) an FCC certified deorbit device, and 4) a solar array deployment system. Three of these missions will be launched in 2018. ...
STTR Phase II 2019 Department of DefenseAir Force -
Highly-Scalable Computational-Based Engineering Algorithms for Emerging Parallel Machine Architectures
SBC: RNET TECHNOLOGIES INC Topic: AF10BT13ABSTRACT: RNET and The Ohio State University propose to use algorithmic modifications and multi-level parallelization techniques and tools to improve the scalability of the aero-line/aero-elastic coupled CFD/CSD codes relevant to the DoD/AF (e.g., CREATE/Kestrel). The optimizations will address inter-node and intra-node parallelization to better target emerging compute architectures (e.g., multi ...
STTR Phase II 2013 Department of DefenseAir Force -
Information Geometric Network Architecture for Heterogeneous Network Management
SBC: Intelligent Automation, Inc. Topic: AF08T011We present a comprehensive framework for modeling, optimization and design for heterogeneous networks. The proposed solution aims to effectively address the existing limitations inherited from the generalized network utility maximization (GNUM) framework. In general, GNUM is a unifying mathematical model as it combines different objectives and constraints from different layers into a single global ...
STTR Phase II 2010 Department of DefenseAir Force -
Monochromatic Light Illuminated High-Speed Digital Image Correlation System for Full-field, High Temperature Strain and Displacement Measurement
SBC: Intelligent Automation, Inc. Topic: AF08BT04High temperature deformation and strain are important measures for characterizing behaviors of structural components under high temperature condition. Measuring full-field, high temperature deformation and strain can lead to a better understanding structural and material response, damage initiation, progressive damage, and ultimately limit state attainment in moderately high temperature material s ...
STTR Phase II 2010 Department of DefenseAir Force -
Plasmonic Cavity Spectroscopic Polarimeter
SBC: ITN ENERGY SYSTEMS, INC. Topic: AF08T027This Small Business Technology Transfer program will develop a spectroscopic polarimeter-on-a-chip using novel plasmonic resonant cavities sensitive to linear polarization over a narrow wavelength range. Spectral selection will be possible through geometric scaling, with this work concentrating on the visible to near infrared wavelength band. Dielectric gratings with subwavelength period will act ...
STTR Phase II 2010 Department of DefenseAir Force -
Information Geometric Network Architecture for Heterogeneous Network Management
SBC: Intelligent Automation, Inc. Topic: AF08T011We present a comprehensive framework for modeling, optimization and design for heterogeneous networks. The proposed solution aims to effectively address the existing limitations inherited from the generalized network utility maximization (GNUM) framework. In general, GNUM is a unifying mathematical model as it combines different objectives and constraints from different layers into a single global ...
STTR Phase II 2010 Department of DefenseAir Force -
A Trusted Computing Framework for Embedded Systems
SBC: Intelligent Automation, Inc. Topic: AF11BT15ABSTRACT: The damage and loss caused by attacks and security breaches have drawn attentions to develop secure and reliable systems for embedded systems. Compared to their desktop counterparts, embedded devices are facing more security challenges, such as the more possible physical access to a target device and more constrained computing environment (e.g., limited RAM and CPU power). Together, the ...
STTR Phase II 2013 Department of DefenseAir Force -
Adaptive Markov Inference Game Optimization (AMIGO) for Rapid Discovery of Evasive Satellite Behaviors
SBC: INTELLIGENT FUSION TECHNOLOGY, INC. Topic: AF17CT02Space superiority requires space protection and space situational awareness (SSA), which rely on rapid and accurate space object behavioral and operational intent discovery. The presence of adversaries in addition to real-time and hidden information constraints greatly complicates the decision-making process in controlling both ground-based and space-based Air Force surveillance assets. The focus ...
STTR Phase II 2019 Department of DefenseAir Force -
Rapid Discovery of Evasive Satellite Behaviors
SBC: Data Fusion & Neural Networks, LLC Topic: AF17CT02The problem addressed in this effort is to automatically learn historical ephemeris space catalog time, position, and velocity entity track update error uncertainties (i.e., without track error covariances) and to automatically (e.g., without expert event labeling) produce: – unmodeled non-gravitational space catalog update flags – abnormal unmodeled catalog update flags with abnorma ...
STTR Phase II 2019 Department of DefenseAir Force -
HASLOC: Hierarchical And-Or Structures for Localization and Object Recognition
SBC: Intelligent Automation, Inc. Topic: AF18AT014Target detection and recognition is a challenging problem because of changes in appearance, viewing direction, occlusion and other covariates. Systems that can accurately and efficiently detect and track objects can provide several benefits in surveillance, monitoring and other applications. As part of this effort, we propose to develop a robust learning-based approach to detect, track and recogni ...
STTR Phase II 2019 Department of DefenseAir Force