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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. Methodologies for Cost-Effective Measurement of Dynamic Material Properties or Characterization of Materials under Dynamic Loads

    SBC: KARAGOZIAN & CASE, INC.            Topic: MDA16T003

    Karagozian & Case, Inc. (K&C) and the Georgia Institute of Technology (Georgia Tech) will develop a re-usable, cost-effective, and accurate dynamic characterization methodology capable of measuring the dynamic material properties of various materials of interest under very high strain rates. Materials property data for various ductile materials (e.g., steel and aluminum) are required as input to f ...

    STTR Phase I 2017 Department of DefenseMissile Defense Agency
  2. Programmable Multi-Frequency Transmitter

    SBC: Space Micro Inc.            Topic: MDA16T005

    Space Micro and partner institution Arizona State University propose to design and prototype a Programmable Multi-Frequency Transmitter (PMFT) that is compliant with both the Kill Vehicle Modular Open Architecture (KVMOA) and Space Telecommunications Radio System (STRS) standards. The KVMOA maximizes reuse of components and system designs and reduce total ownership costs. The STRS standard allows ...

    STTR Phase I 2017 Department of DefenseMissile Defense Agency
  3. Deep Learning with Whole-Scene Contextual Reasoning for Target Characterization

    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
  4. Dim Target Extraction and Conjoint Tracking (DTECT) Enhancements for Missile Defense Applications

    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
  5. 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
  6. Development of powder bed printing (3DP) for rapid and flexible fabrication of energetic material payloads and munitions

    SBC: MAKEL ENGINEERING, INC.            Topic: DTRA16A001

    This program will demonstrate how additive manufacturing technologies can be used with reactive and high energy materials to create rapid and flexible fabrication of payload and munitions. Our primary approach to this problem will be to use powder bed binder printing techniques to print reactive structures. The anticipated feedstock will consist of composite particles containing all reactant spe ...

    STTR Phase I 2016 Department of DefenseDefense Threat Reduction Agency
  7. Innovative Mitigation of Radiation Effects in Advanced Technology Nodes

    SBC: RELIABLE MICROSYSTEMS LLC            Topic: DTRA16A003

    Establish a radiation-aware analysis capability in a commercial EDA design flow that will enable first-pass success in radiation-hardened by design (RHBD) for DoD ASICs in much the same way that existing EDA design suites ensure first pass functionality and performance success of complex ASICs destined for commercial applications. Layout-aware, calibrated single-event radiation models that captur ...

    STTR Phase I 2016 Department of DefenseDefense Threat Reduction Agency
  8. Modular Pulse Charger and Laser Triggering System for Large-Scale EMP and HPM Applications

    SBC: SCIENTIFIC APPLICATIONS & RESEARCH ASSOCIATES, INC.            Topic: DTRA16A004

    For effective protection against EMP and HPM threats, it is important to understand the physics of the threats, and also to quantify the effects they have on electrical systems. EMP and HPM vulnerability testing requires delivery of high peak power and electric fields to distant targets. The most practical solution to simulate such environments is to develop a modular, optically-isolated MV-antenn ...

    STTR Phase I 2016 Department of DefenseDefense Threat Reduction Agency
  9. 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
  10. 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
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