You are here
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.
SBC: FREENT TECHNOLOGIES, INC. Topic: MDA13015
FreEnt Technologies, Inc. (FreEnt) and Johns Hopkins Universitys Applied Physics Laboratory (APL) are proposing a multiple-hit detection sensor called the Optical Lethality Measurement System (OLMS). This system is based on the Planar Optical Penetration Sensor (POPS) technology (originally developed and patented by APL) and prior art associated with the Blast Initiation Detector (BID). The BID is ...STTR Phase II 2017 Department of DefenseMissile Defense Agency
SBC: GCAS, Inc. Topic: MDA13T001
Our 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
SBC: EXOANALYTIC SOLUTIONS INC Topic: MDA15T001
ExoAnalytic 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
SBC: TOYON RESEARCH CORPORATION Topic: MDA12T004
Overhead Persistent Infrared (OPIR) platforms observe challenging threat and scene phenomenology. Toyon Research Corporation developed an image processing framework for clutter estimation/suppression and track-before-detect to jointly detect and track targets. The Target Extraction and Conjoint Tracking application, developed under initial Phase II funding and demonstrated using real-world data so ...STTR Phase II 2017 Department of DefenseMissile Defense Agency
Efficient Clutter Suppression and Nonlinear Filtering Techniques for Tracking Objects in the Presence of DebrisSBC: TOYON RESEARCH CORPORATION Topic: MDA12T004
Toyon developed a Phase I framework leveraging spatiotemporal image processing algorithms for non-stationary clutter estimation, and nonlinear filtering based Track-before-Detect algorithms for tracking targets. Information is fused across sensors without loss of information due to detection thresholds. Algorithms, when applied jointly, provide a near-optimal solution. In addition, algorithms a ...STTR Phase II 2014 Department of DefenseMissile Defense Agency
Enhancement of Ballistic Missile Defense System Level Simulation Operations Through Multi-core ProcessingSBC: ISSAC Corp Topic: MDA13T003
The ISSAC Team propose a novel method to encapsulate legacy models and simulations that allows these components to take advantage of modern, multi-core, multi-processor hardware suites. Encapsulating these legacy codes provides 3 primary advantages to deal with complex systems and systems of systems (Air Force, Navy, Department of Homeland Security (DHS), Federal Emergency Management Agency (FEMA) ...STTR Phase II 2016 Department of DefenseMissile Defense Agency
SBC: Stottler Henke Associates, Inc. Topic: MDA12T002
The ultimate goal of this proposed effort is to better utilize disparate sensor data to perform better correlations and lethality assessments through the development of a sensor data fusion system using artificial intelligence (AI) techniques and the concept of extracting features from raw sensor data and reasoning about those features and their hypothetical association with hypothesized objects. ...STTR Phase II 2014 Department of DefenseMissile Defense Agency
SBC: SAN DIEGO COMPOSITES, INC. Topic: MDA13T007
The goal of this program is to design a lightweight optical bench capable of remaining stable under temperature and moisture changes, while isolating the precision optical array from vibrations such as engine noise and air turbulence. By integrating a customizable periodic stack in the bench, vibrations are attenuated more effectively than commercially available mounts. Additionally, the periodic ...STTR Phase II 2016 Department of DefenseMissile Defense Agency
SBC: CFD RESEARCH CORPORATION Topic: MDA14T002
Thermally induced fatigue and residual stress introduced during fabrication are sources of failure in microelectronics, which raises reliability concerns for MDA and its system integrators. CFDRC has teamed with experts in the reliability of microelectronics packaging to develop a physics based modeling and testing protocol to correlate material properties and thermal loading conditions to stress ...STTR Phase II 2016 Department of DefenseMissile Defense Agency
SBC: DECIBEL RESEARCH, INC. Topic: MDA12T002
Under the Phase I effort, a set of algorithms were developed/enhanced that, when integrated into a fused track and characterization schema, are capable of realizing the full potential performance afforded by the battle manager having multiple sensors. dBWager is a multi-sensor measurement correlation algorithm that provides highly accurate state vector estimates and provides the correlation of e ...STTR Phase II 2014 Department of DefenseMissile Defense Agency