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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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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 -
SOCRATES Maritime Multi-access Optical Communication System
SBC: SA PHOTONICS, LLC Topic: N16AT024SA Photonics is pleased to propose the SOCRATES free space optical communication and sensing system featuring the Photonic Optical Multicast Mast Unit (POMMU). SOCRATES enables 360 degree multicast capability of high bandwidth communication in addition to threat search and tracking capability. SA Photonics will team with Prof. Michael Kudenov at North Carolina State University who will investigate ...
STTR Phase II 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 -
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 -
Target Tracking via Deep Learning
SBC: TOYON RESEARCH CORPORATION Topic: AF17AT027Persistent tracking of high-value targets is of great interest for reconnaissance and surveillance applications. In recent work, deep neural networks have demonstrated excellent performance on the popular Visual Object Tracking (VOT) challenge; however, these algorithms have not been tested on applications of interest to the Air Force, such as ground vehicle tracking in video recorded from Unmanne ...
STTR Phase I 2017 Department of DefenseAir Force -
Adaptive and Smart Materials for Advanced Manufacturing Methods
SBC: NEXTGEN AERONAUTICS, INC. Topic: AF17AT018Additive manufacturing (AM) technologies covering a broad range of technologies and processes have been under continuous and accelerating development since the 80s. While there are still fundamental hurdles such as low production rates and small sizes, AM holds tremendous promise in terms of revolutionizing manufacturing. Recent trends include direct-printing and incorporating sensors and electr ...
STTR Phase I 2017 Department of DefenseAir Force -
Alternative Methods for Creating a Sodium Guidestar
SBC: Arete Associates Topic: AF17AT005Adaptive Optics allow ground-based astronomical observatories to overcome atmospheric distortion limited observation by using natural and artificial guide stars to measure the distortion. Sodium-layer guide stars provide near all-sky coverage for high resolution astronomy. Over the last 20 years, Optically Pumped Semiconductor Laser (OPSL), also referred to as Vertically Extended Cavity Surface ...
STTR Phase I 2017 Department of DefenseAir Force -
Polychromatic guide-stars using novel optically pumped semiconductor disk lasers
SBC: Crystalline Mirror Solutions, LLC Topic: AF17AT005During the last two decades, vertical-external-cavity surface-emitting lasers (VECSELs) have emerged as excellent high-power laser sources that combine diode-pumping, broad-pump tolerance, wavelength selectivity, narrow linewidth, broad tunability, high beam quality, compactness, and efficiency into one attractive package. These characteristics make them an ideal candidate for use as more economic ...
STTR Phase I 2017 Department of DefenseAir Force