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 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. Human-Machine Teaming with Machine Learning Algorithms

    SBC: KITWARE INC            Topic: SOCOM18B001

    Characterizing and understanding the interactions between human and machine plays an important role in extracting the most out of our machine learning algorithms while reducing human workload. We propose to develop a software prototype system that reduces user workload of exploiting AI algorithms for imagery exploitation. We will design a user-friendly system for content matching with interactive ...

    STTR Phase II 2020 Department of DefenseSpecial Operations Command
  2. Hardened, Optically-Based Temperature Characterization of Detonation Environments

    SBC: SA PHOTONICS, LLC            Topic: DTRA19B001

    Improving the effectiveness of counter-WMD operations requires improved understanding of weapon-target interaction. Specifically, time-resolved measurements of temperature and composition are required to allow temporal evolution of a detonation fireball. To address this need, SA Photonics will develop MONITOR, a laser-based temperature diagnostic that will enable wide dynamic range temperature mea ...

    STTR Phase I 2020 Department of DefenseDefense Threat Reduction Agency
  3. DOEYK: Detecting Objects with Enhanced YOLOv3 and Knowledge Graph

    SBC: Intelligent Automation, Inc.            Topic: DTRA19B002

    Current state-of-the-art object detection algorithms are almost exclusively based on Deep Convolutional Neural Network (DCNN). These algorithms all require a large amount of labeled examples for each of the object categories they can recognize. These algorithms will fail for novel objects that only very few or even no prior examples are available. These algorithms are also far less accurate when c ...

    STTR Phase I 2020 Department of DefenseDefense Threat Reduction Agency
  4. 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
  5. Fully Metallic Self-Fragmenting Structural Reactive Materials Using Composites and Alloys Comprised of Aluminum, Lithium, and Magnesium

    SBC: Adranos Energetics LLC            Topic: DTRA16A002

    While aluminum casing materials provide some enhanced performance and thermal loading to explosive ordinance, their overall effectiveness is highly limited by incomplete combustion and long residence times. In order to reduce these problems, the casing material must be designed to facilitate rapid fragmentation through either specialized casing geometries or greatly refined initial particle sizes. ...

    STTR Phase I 2016 Department of DefenseDefense Threat Reduction Agency
  6. 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
  7. Compact Laser Drivers for Photoconductive Semiconductor Switches

    SBC: ASR Corporation            Topic: DTRA16A004

    A compact laser driver will allow photoconductive semiconductor switches to be used in small EMP simulator "building blocks" (EMPBB). Combined with a battery powered on-board pulsed power system, these EMPBBs will allow the construction of flexible EMP test facilities with nothing more than a single fiber optic timing connection to each EMPBB.

    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. Data Driven Intent Recognition Framework

    SBC: OTHER LAB, INC.            Topic: NSF13599

    A critical aspect of exoskeleton control that has to date introduced a performance limitation is the ability of the exoskeleton to recognize the intent of the operator so it can apply assistance to their desired motion. This intent recognition effort is typically solved using ad-hoc methods where subject matter experts make design decisions and tune transitions to identify intended maneuvers as re ...

    STTR Phase II 2016 Department of DefenseSpecial Operations Command
  10. Information Salience

    SBC: DISCERNING TECHNOLOGIES, LLC            Topic: OSD11TD1

    Empirical-based mathematical framework and computer algorithms, for representing human perception and cognition processes and limitations, which influence the recognition of salient information about rapidly changing events.

    STTR Phase II 2015 Department of DefenseOffice of the Secretary of Defense
US Flag An Official Website of the United States Government