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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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Carbon Nanotube Technology for RF Amplification
SBC: CARBON TECHNOLOGY INC Topic: AF15AT15Theoretical studies have shown that the electrical current in a CNT Field Effect Transistor (CFET) is intrinsically linear. Inherently linear CNTs offer significant improvements in performance without sacrificing power and have the potential for greatly improving range and sensitivity in state-of-the-art receivers such as those used in satellite systems and other communications applicationsModelin ...
STTR Phase II 2017 Department of DefenseAir Force -
Cognitive Adaptation and Mission Optimization (CAMO) for Autonomous Teams of UAS Platforms
SBC: OPTO-KNOWLEDGE SYSTEMS INC Topic: N17BT035OKSI and Professor Matthew Taylor will develop the Cognitive Adaptation and Mission Optimization (CAMO) command and control tool for teams of UAS platforms. CAMO will incorporate existing databases (e.g., NASA population maps, FAA airspace maps, etc.) as well as real-time data from UAS into a learning-based cognitive control solution that maximizes mission performance while minimizing risk for a t ...
STTR Phase I 2017 Department of DefenseNavy -
Cognitive Risk Management for UAS Missions
SBC: Stottler Henke Associates, Inc. Topic: N17BT035Enabling operators to command and control multiple UAVs will require higher levels of supervisory control, enabling vehicles to operate autonomously during larger portions of each mission. For the foreseeable future, however, critical portions of each mission will require operators to apply their superior knowledge, judgment, and skills to assess the situation, monitor execution more closely and, ...
STTR Phase I 2017 Department of DefenseNavy -
CyberSTEPS- Cyber Skills Training with Electronic Performance Support
SBC: Tier 1 Performance Solutions, LLC Topic: AF16AT08There are many challenges in creating Air Force systems that are resilient against cyber threats. The cyber environment and its threats are highly dynamic, requiring practices and training to be dynamic as well. Cyber threats must be considered during th...
STTR Phase I 2016 Department of DefenseAir Force -
3D Acoustic Model for Geometrically Constrained Environments
SBC: HEAT, LIGHT, AND SOUND RESEARCH, INC. Topic: N16AT018Systems that operate in constrained environments depend on the acoustics in several ways. Harbor defense systems detect intruders (people and/or vessels) by either listening for their noises (passively) or by pinging on them and detecting their echoes (actively). Furthermore, such systems may also form the equivalent of an underwater cell phone network using sound to carry the information. The aco ...
STTR Phase I 2016 Department of DefenseNavy -
3D Acoustic Model for Geometrically Constrained Environments
SBC: HEAT, LIGHT, AND SOUND RESEARCH, INC. Topic: N16AT018Systems that operate in constrained environments depend on the acoustics in several ways. Harbor defense systems detect intruders (peopleand/or vessels) by either listening for their noises (passively) or by pinging on them and detecting their echoes (actively). Furthermore, suchsystems may also form the equivalent of an underwater cell phone network using sound to carry the information. The acous ...
STTR Phase II 2017 Department of DefenseNavy -
Data Driven Intent Recognition Framework
SBC: OTHER LAB, INC. Topic: NSF13599A critical aspect of exoskeleton control that has to date introduced a performance limitation is the ability of the exoskeleton to recognize the intent of the operator so it can apply assistance to their desired motion. This intent recognition effort is typically solved using ad-hoc methods where subject matter experts make design decisions and tune transitions to identify intended maneuvers as re ...
STTR Phase II 2016 Department of DefenseSpecial Operations Command -
Decision Making under Uncertainty
SBC: GCAS, Inc. Topic: MDA13T001Our proposed second order uncertainty (SOU) product is a decision making software solution that addresses the problem of providing accurate and precisely defined decision courses of action (COAs) of complex, time-constrained problems in a fraction of the time required by alternative methods striving to achieve the same level of precision. Complex decision situations can deal with large volume of ...
STTR Phase II 2016 Department of DefenseMissile Defense Agency -
Deep Learning with Whole-Scene Contextual Reasoning for Target Characterization
SBC: EXOANALYTIC SOLUTIONS INC Topic: MDA15T001ExoAnalytic Solutions is developing DEEPR (Deep Learning with Whole-Scene Contextual Reasoning for Object Characterization), an advanced multi-sensor multi-object classifier for integrated object characterization. The overall objective of DEEPR is to develop a suite of advanced, novel techniques that combine innovative advances in deep, hierarchical machine learning together with recurrent Deep L ...
STTR Phase II 2017 Department of DefenseMissile Defense Agency -
Degraded Synthetic Training Using an Integrated Kinetic-Cyber Training Environment
SBC: Scalable Network Technologies, Inc. Topic: N17AT023Integration of kinetic training and cyber training will provide a unified platform for combined cyberspace/kinetic battlefield training for our warfighters. Such a training platform will support high-fidelity, multi-factor simulated engagements in which the trainee can be exposed to all domains that are simultaneously interacting with each other. Existing approaches do not accurately reflect the d ...
STTR Phase I 2017 Department of DefenseNavy