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The Award database is continually updated throughout the year. As a result, data for FY24 is not expected to be complete until March, 2025.

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.

  1. Lightweight, Stable Optical Bench with Integrated Vibration Attenuation

    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
  2. Interactive Sensor Fusion for Context-Aware Discrimination

    SBC: OPTO-KNOWLEDGE SYSTEMS INC            Topic: MDA15T001

    We propose a novel computational framework for discrimination that incorporates sensor data from observations of the engagement and from kill assessment (KA) that such sensors can provide. The KA information is combined with data from other sensors to improve the discrimination decision and to reduce the probability of correlated shots. Approved for Public Release 16-MDA-8620 (1 April 16)

    STTR Phase I 2016 Department of DefenseMissile Defense Agency
  3. Deep Inference and Fusion Framework Utilizing Supporting Evidence (DIFFUSE)

    SBC: BOSTON FUSION CORP            Topic: MDA15T001

    Combining information from disparate sensors can lead to better situational awareness and improved inference performance; unfortunately, traditional multi-sensor fusion cannot capture complex dependencies among different objects in a scene, nor can it exploit context to further boost performance. Integrating context information within a fusion architecture to reason cohesively about scenes of inte ...

    STTR Phase I 2016 Department of DefenseMissile Defense Agency
  4. Robust Classification through Deep Learning and Dynamic Multi-Entity Bayesian Reasoning

    SBC: EXOANALYTIC SOLUTIONS INC            Topic: MDA15T001

    Missile defense faces the challenges of rapidly maturing and evolving complex threats, possessing capabilities which require the use of all available resources to successfully detect, track and identify the lethal objects. Future performance will rely on multiple sensors such as ground and sea based radars and electro-optical and infrared sensors for target recognition. It is crucial to develop a ...

    STTR Phase I 2016 Department of DefenseMissile Defense Agency
  5. Decision Making under Uncertainty

    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
  6. Real-Time Health Management Portable Sensor for Solid Rocket Motors

    SBC: PHYSICAL SCIENCES INC.            Topic: MDA14T004

    Physical Sciences Inc. (PSI) proposes to design, develop, and demonstrate a portable, non-invasive, real-time sensor to assess the chemical and physical health of solid rocket motors as a function of age without affecting the motors integrity nor having direct contact with the propellant. In Phase II, a sensor to monitor specific gas species that are markers of the chemical and mechanical aging pr ...

    STTR Phase II 2016 Department of DefenseMissile Defense Agency
  7. Decision Making under Uncertainty

    SBC: GCAS, Inc.            Topic: MDA13T001

    The objectives of our Phase I effort are to characterize target sensor measurement uncertainties and feature extraction uncertainties; determine how and where, in the processing chain, these affect target discrimination and classification; show how the different sources of uncertainty lead to the cumulative uncertainty in the final decision; provide techniques that will be instrumental to optimizi ...

    STTR Phase I 2014 Department of DefenseMissile Defense Agency
  8. Adaptive Management and Mitigation of Uncertainty in Fusion (AMMUF)

    SBC: CHARLES RIVER ANALYTICS, INC.            Topic: MDA13T001

    Missile defense takes place in an uncertain and dynamic environment, so multi-sensor fusion must be employed to aggregate and merge disparate data from the battlefield. However, the fusion process is hindered by the vast amount of uncertainty in operational contexts, such as imprecise measurements and varying environmental conditions. Various algorithms and fusion processes have been developed to ...

    STTR Phase I 2014 Department of DefenseMissile Defense Agency
  9. Uncertainty Characterization Using Copulas (UC)2

    SBC: BOSTON FUSION CORP            Topic: MDA13T001

    Boston Fusion, together with our teammate Syracuse University, propose a program of research and development, namely Uncertainty Characterization Using Copulas, which will lead to a parametric framework based on the statistical theory of copulas for modeling uncertainties in a centralized fusion architecture for the problem of target classification for ballistic missile defense applications. This ...

    STTR Phase I 2014 Department of DefenseMissile Defense Agency
  10. Decision Making Under Uncertainty

    SBC: Systems & Technology Research LLC            Topic: MDA13T001

    The proposed effort will develop a new approach to characterize and analyze multiple-sensor decision making under uncertainty. The major focus will be on the decision architecture involving multiple Ballistic Missile Defense (BMD) elements and the evaluation of the performance of various decision architectures for ballistic missile object discrimination. The proposed method will provide a well-d ...

    STTR Phase I 2014 Department of DefenseMissile Defense Agency
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