You are here

Award Data

For best search results, use the search terms first and then apply the filters
Reset

The Award database is continually updated throughout the year. As a result, data for FY20 is not expected to be complete until September, 2021.

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.

  1. Algorithms for Look-down Infrared Target Exploitation

    SBC: SIGNATURE RESEARCH, INC.            Topic: 1

    Signature Research, Inc. (SGR) and Michigan Technological University (MTU) propose a Phase I STTR effort to develop a learning algorithm which exploits the spatio-spectral characteristics inherent within IR imagery and motion imagery.Our archive of modelled and labeled data sets will allow our team to thoroughly capture the variable elements that will drive machine learning performance.The overall ...

    STTR Phase I 2018 Department of DefenseNational Geospatial-Intelligence Agency
  2. Volume Digital Holographic Wavefront Sensor

    SBC: NUTRONICS, INC.            Topic: AF18AT006

    Nutronics, Inc. and Montana State University propose to develop and evaluate computational methods for a Volume Digital Holographic Wavefront Sensor (VDHWFS).VDHWFS based imaging offers the potential to provide the equivalent of wide field of view adaptive optics (AO) compensated imaging, but without the added complexity of AO components and hardware.Recent result for coherent imaging developed by ...

    STTR Phase I 2018 Department of DefenseAir Force
  3. Non-Linear Adaptive Optics (NLAO)

    SBC: NUTRONICS, INC.            Topic: AF18AT008

    Nutronics, Inc. and Montana State University propose to develop an approach for non-linear control of hysteresis and incorporate (if necessary) integrated Multi-Input-Multi-Output real time control with this capability.Our control systems already include a proven high speed real time control approach to determine the optimal set of actuator commands that satisfy inter-actuator stroke limitations.O ...

    STTR Phase I 2018 Department of DefenseAir Force
  4. Stable High Bandwidth AO Control with physical DM constraints

    SBC: Guidestar Optical Systems, Inc.            Topic: AF18AT008

    Adaptive optics (AO) system performance is hindered by the mechanical limits of the deformable mirror (DM), namely stroke limits, interactuator stroke limits, and mechanical resonance.The nature of the multi-in multi-out (MIMO) control system does not lend itself well to notch filters to combat the mechanical resonances, and the stroke limits introduce non-linearities to the system.The traditional ...

    STTR Phase I 2018 Department of DefenseAir Force
  5. HASLOC: Hierarchical And-Or Structures forLocalization and Object Recognition

    SBC: INTELLIGENT AUTOMATION, INC.            Topic: AF18AT014

    Target 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 I 2018 Department of DefenseAir Force
  6. Additive Manufacturing Sensor Fusion Technologies for Process Monitoring and Control.

    SBC: X-Wave Innovations, Inc.            Topic: DLA18A001

    Additive Manufacturing (AM) is a modern and increasingly popular manufacturing process for metallic components, but suffers from well known problems of inconsistent quality of the finished product. Process monitoring and feedback control are therefore crucial research areas with a goal of solving this problem. To address this concern, X-wave Innovations, Inc. (XII) and the University of Dayton Res ...

    STTR Phase I 2018 Department of DefenseDefense Logistics Agency
  7. Rapid Identification of Effects of Defects within Metal Additive Manufacturing (RIED-AM)

    SBC: INTELLIGENT AUTOMATION, INC.            Topic: N18AT013

    Additive manufacturing (AM) systems, especially metal AM, bring revolutionary capabilities, but suffer from a lack of understanding of the defects that exist within the components. In this research, based on selective experimental study and numerical simulations, we will develop an empirical database of defects and their effects on mechanical properties using Laser Powder Bed Fusion (LPBF) technol ...

    STTR Phase I 2018 Department of DefenseNavy
  8. Situational Awareness for Mission Critical Ship Systems using Probabilistic Knowledge Graph

    SBC: INTELLIGENT FUSION TECHNOLOGY, INC.            Topic: N18AT009

    This effort proposes to develop situational awareness methodologies for mission critical ship system based on the state-of-the-art probabilistic knowledge graph (KG) and deep learning. The proposed KG approach can incorporate various data fusion technologies for analysis of unstructured data (text, images, etc.) and structured data (signal feeds, database items, etc.) for automated decision suppor ...

    STTR Phase I 2018 Department of DefenseNavy
  9. Full Featured Low-Cost HMS for Combatant Craft

    SBC: QUALTECH SYSTEMS, INC.            Topic: N18AT015

    Qualtech Systems, Inc. (QSI), in collaboration with VU proposes to develop a state-of-the art HMS system featuring: (1) Low Hardware cost by leveraging industrial-grade computers ruggedized to military specifications (2) Low Software cost by leveraging QSI’s COTS TEAMS software with real-time monitoring and diagnosis capabilities (3) Vibration and Shock Analysis and its impact on vehicle and cre ...

    STTR Phase I 2018 Department of DefenseNavy
  10. System for Nighttime and Low-Light Face Recognition

    SBC: MUKH Technologies LLC            Topic: SOCOM18A001

    Recognizing faces in low-light and nighttime conditions is a challenging problem due to the noisy and poor quality nature of the images.Thermal imaging is often used to obtain facial biometric in such conditions. Thermal face images, while having a strong signature at nighttime, are not typically maintained in biometric-enabled watch lists and so must be compared with visible-light face images to ...

    STTR Phase I 2018 Department of DefenseSpecial Operations Command
US Flag An Official Website of the United States Government