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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.

  1. 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
  2. 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
  3. 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
  4. Microelectronics Component Adhesive Selection and Design Rules for Failure Avoidance

    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
  5. Novel Structure-Preserving Algorithms for Accurate Rocket Trajectory Propagation

    SBC: OPTIMAL SYNTHESIS INC.            Topic: MDA17T002

    The Department of Defense uses large-scale high-resolution federated simulations to propagate rocket vehicle trajectories. Runge-Kutta methods have served as a de-facto standard while conducting such simulations. However, there are several challenges while using Runge-Kutta methods for this task. Firstly, there should be exact time-step matching between federates, otherwise the states have to be i ...

    STTR Phase I 2018 Department of DefenseMissile Defense Agency
  6. Lightweight Structural Components of a Missile Body

    SBC: ALPHASTAR TECHNOLOGY SOLUTIONS LLC            Topic: MDA17T004

    The Ground-Based Interceptor (GBI) missile is the weapon component of the Ground-Based Midcourse Defense (GMD) system that consists of a rocket booster and kinetic kill vehicle. Recently, MDA has sought technologies to improve the performance of the booster vehicle (BV). To date, studies have shown that reductions in weight have a direct impact on overall effectiveness. The current proposal aims t ...

    STTR Phase I 2018 Department of DefenseMissile Defense Agency
  7. Deep Machine learning for risk Analysis and Prediction (D-MAP) in supply chains

    SBC: Intelligent Automation, Inc.            Topic: MDA16T002

    Globalization and digitization have been driving the recent economic growth at the expense of raising the risk level in the supply chain related to fraud, security, and safety, while current practice of supply chain management and risk assessment is lagging far behind. Therefore, commercial industries and government agencies are seeking advanced supply chain risk assessment solutions, which can ef ...

    STTR Phase II 2018 Department of DefenseMissile Defense Agency
  8. Programmable Multi-Frequency Transmitter for Missile Communciations

    SBC: Space Micro Inc.            Topic: MDA16T005

    Improving capabilities of telemetry systems for next generation e.g. (MOKV) missile defense launch vehicles, kill vehicles, and test/target vehicles subsystems can transform operational testing of such systems and has the potential to increase capabilities of systems that rely on radio communications. As these systems, and their test scenarios become get more complex they will require unprecedente ...

    STTR Phase II 2018 Department of DefenseMissile Defense Agency
  9. SmallSat Stirling Cryocooler for Missile Defense (SSC-X)

    SBC: WECOSO, INC.            Topic: MDA17T003

    West Coast Solutions (WCS), in collaboration with the Georgia Institute of Technology and Creare LLC, proposes an adaptation of our SmallSat Stirling Cryocooler (SSC) technology in response to STTR Topic MDA17-T003: High-Efficiency, Low-Volume, Space-Qualified Cryogenic-Coolers. In Phase 1 we will scale up a design currently in development for NASA to meet the Missile Defense Agency (MDA) topic re ...

    STTR Phase I 2018 Department of DefenseMissile Defense Agency
  10. Trajectory Simulation using PSM

    SBC: TRITON SYSTEMS, INC.            Topic: MDA17T002

    Triton Systems, Inc. proposes to develop a method for efficiently running federated simulations of atmospheric and orbital rocket flight. Tritons proposed method will be able to get information between time steps without the need for interpolation and will significantly reduce the computational time needed to run Federated simulations.Approved for Public Release | 18-MDA-9522 (23 Feb 18)

    STTR Phase I 2018 Department of DefenseMissile Defense Agency
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