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Award Data
The Award database is continually updated throughout the year. As a result, data for FY22 is not expected to be complete until September, 2023.
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.
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Integrated learning-based and regularization-based super resolution for extreme MWIR image enhancement
SBC: OPTO-KNOWLEDGE SYSTEMS INC Topic: N17AT016OKSI and Northwestern University propose to develop a single-image super-resolution (SR) methodology for mid-wave infrared (MWIR) imagery that combines learning-based and regularization-based approaches to produce extreme enhancement of low-resolution images. We will also develop a detector-limited imaging system specifically designed to be used with the SR methodology for which even higher levels ...
STTR Phase II 2019 Department of DefenseNavy -
Advanced Command and Control Architectures for Autonomous Sensing
SBC: TOYON RESEARCH CORPORATION Topic: N18BT030We propose to develop an innovative open architecture for the semi-autonomous command and control (C2) of teaming Unmanned Aircraft Systems (UAS). The proposed architecture, based upon Toyon’s Decentralized Asset Management system, supports both centralized and decentralized fusion and control autonomy solutions as well as hybrids approaches. Leveraging STANAG-4586, TCP/IP, UPD, Google™ protob ...
STTR Phase I 2019 Department of DefenseNavy -
Blending Classical Model-Based Target Classification and Identification Approaches with Data-Driven Artificial Intelligence
SBC: TOYON RESEARCH CORPORATION Topic: N18BT033Toyon Research Corp. and the University of California propose to develop innovative algorithms to perform automatic target recognition (ATR), localization, and classification of maritime and land targets in EO/IR, LiDAR, and SAR imagery. The proposed algorithms are based on recent developments made at the University of California, which outline a strong mathematical framework for naturally blendin ...
STTR Phase I 2019 Department of DefenseNavy -
Embedded Space Analytics
SBC: INFOBEYOND TECHNOLOGY LLC Topic: N16AT020Navy needs a real-time graph embedding tool for analyzing huge graphs (millions of nodes and billions of edges) from diverse sources. However, current approaches cannot provide dynamic and scalable graph analytics to signify the military value of tactical data. In this project, InfoBeyond advocates EStreaming (Embedding & Streaming) for scalable and efficient graph streaming. EStreaming promotes b ...
STTR Phase II 2017 Department of DefenseNavy -
Fast and Flexible Differential Equation Model Fitting with Application to Pharmacometrics
SBC: Metrum Research Group LLC Topic: N16AT016We are developing a platform for pharmacometric data analysis workflow that is much more flexible and efficient than anything else on the market. This will be accomplished by (1) developing new functions within Stan, a widely used, open-source, probabilistic programming language and Bayesian inference engine, for computationally efficient data analysis using complex differential equation models, ( ...
STTR Phase II 2017 Department of DefenseNavy -
Production of Chemical Reagents for Prompt-Agent-Defeat Weapons
SBC: NALAS ENGINEERING SERVICES INC Topic: DTRA14B001Nalas Engineering and Johns Hopkins University collaborated in a Phase I STTR program to study reactive mixtures of HI3O8 and nanocomposite fuels previously developed by the Weihs Group. These fuel/oxidizer mixtures are uniquely able to simultaneously produce heat and biocidal iodine gas, a combination designed to destroy biological weapons. The team at Nalas focused on evaluating conditions for p ...
STTR Phase II 2017 Department of DefenseDefense Threat Reduction Agency -
Risk-Based Unmanned Air System (UAS) Mission Path Planning Capability
SBC: ACTA, LLC Topic: N17BT034In this Phase I Project ACTA and its partners will demonstrate the feasibility of developing a risk-based mission path planning (RB MPP) approach. Areas of interest to the Navy where a RB MPP address critical needs include enabling less restrictive UAS operations within the US National and Foreign Airspaces. The Phase I will demonstrate feasibility with a two-step approach. The first step will dem ...
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 -
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 -
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