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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. Topological Data Analysis for Automated Annotation of EO/SAR Datasets

    SBC: ARETE ASSOCIATES            Topic: NGA203005

    In recent years, it has become increasingly important to conduct Geospatial Intelligence (GEOINT) operation via commercial and government persistent sensor systems, which have produced a copious amount of data relevant to the National Geospatial-Intelligence Agency (NGA). As the supply of data expands, it is necessary to employ automated analytics to exploit the data efficiently. We cannot rely on ...

    SBIR Phase I 2021 Department of DefenseNational Geospatial-Intelligence Agency
  2. Handheld Celestial Navigation System

    SBC: ARETE ASSOCIATES            Topic: SOCOM203002

    Modern navigation systems are heavily reliant on satellites (e.g., GPS, GNSS, GLONASS, etc.) to maintain positional awareness and orientation. These signals are susceptible to intentional disruption, such as jamming or spoofing, and unintentional interruption due to radio frequency interference, signal attenuation caused by local terrain, or satellite malfunctions. Under Phase I of this SBIR, Aret ...

    SBIR Phase I 2021 Department of DefenseSpecial Operations Command
  3. Dynamic Parameter Selection for Community Detection Algorithms (Graph Networks)

    SBC: ARETE ASSOCIATES            Topic: NGA212002

    In the pattern of life problem space, data is often represented via mathematical graphs, in which a variety of algorithms may be employed to conduct semi-autonomous analysis. While successful empirical application of graph-domain algorithms on ABI problems has been achieved, most of these algorithms require a tuning parameter, which is often set heuristically in real-world scenarios. Arete has dev ...

    SBIR Phase I 2022 Department of DefenseNational Geospatial-Intelligence Agency
  4. Frequency Hopper/DSSS Detection

    SBC: TECHNOLOGY SERVICE CORP            Topic: N/A

    "Modern low-probability of intercept (LPI) signals, such as spread spectrum frequency hopping and direct sequence coded waveforms (FHSS/DSSS), typified by wireless cell phone, IEEE 802.11, and Bluetooth signals, pose a serious challenge to conventionalsignal interceptors. Since Special Operations Forces (SOF) must continuously monitor such signals in a variety of tactical situations worldwide, no ...

    SBIR Phase I 2002 Department of DefenseSpecial Operations Command
  5. Automated Feature Extraction Capabilities for the Development of High-Resolution GEOINT Feature Data and Constructing Correlated Databases

    SBC: TECHNOLOGY SERVICE CORP            Topic: SOCOM06012

    Data resources available for automatic feature extraction (AFE) have expanded significantly in the last few years. Available sensor data now includes high-resolution multispectral and hyperspectral sensors, synthetic aperture radar (SAR), and accurate height measurement sensors such as LIDAR and interferometric SAR (IFSAR). Current AFE tools are unable to fuse and process all the new types of se ...

    SBIR Phase I 2006 Department of DefenseSpecial Operations Command
  6. Tactical Sensor Data Processing, Exploitation, and Dissemination

    SBC: CINTEL INC            Topic: SOCOM163008

    The U.S. Special Operations Command (USSOCOM) trains, equips and deploys Special Operations Forces (SOF) to worldwide locations to advance the nation's interests. The reality of worldwide operations requires a worldwide intelligence gathering and analysis capability, a processing capability and a way to disseminate actionable intelligence to operational units. Our solution will directly supp ...

    SBIR Phase I 2017 Department of DefenseSpecial Operations Command
  7. Bounding generalization risk for Deep Neural Networks

    SBC: EULER SCIENTIFIC            Topic: NGA20A001

    Deep Neural Networks have become ubiquitous in the modern analysis of voluminous datasets with geometric symmetries. In the field of Particle Physics, experiments such as DUNE require the detection of particle signatures interacting within the detector, with analyses of over a billion 3D event images per channel each year; with typical setups containing over 150,000 different channels.  In an ...

    STTR Phase I 2020 Department of DefenseNational Geospatial-Intelligence Agency
  8. Transparent Emissive Microdisplay

    SBC: ATOMINC INC            Topic: SOCOM163009

    This Small Business Innovation Research Phase I project aims to undertake feasibility study of design and fabrication a full-color, transparent, emissive display technology with pixel-pitch of 20m (or smaller), and an area which exceeds the image intensifiers 18mm circular effective area for use in a multi-imaging plane system. This includes identifying the technology utilized; detailing the techn ...

    SBIR Phase I 2017 Department of DefenseSpecial Operations Command
  9. Improved System and Methods for Evaluating Protective Material Performance to Chemical Agents

    SBC: SENSOR RESEARCH AND DEVELOPMENT CORP            Topic: N/A

    "Sensor Research and Development Corporation (SRD) proposes to develop an Automated Measurement of Breakthrough in Real-time (AMBR) prototype to test chemical protective materials. AMBR will increase the safety, efficiency, and sample throughput for fabrictests while improving data quality and expanding test capabilities. SRD will develop AMBR by integrating proven solid-state chemical agent sen ...

    SBIR Phase I 2002 Department of DefenseOffice for Chemical and Biological Defense
  10. Lightweight, Compact Atmospheric Gas Sensor

    SBC: SENSOR RESEARCH AND DEVELOPMENT CORP            Topic: SOCOM08005

    SRD will develop a miniaturized atmospheric gas sensor array and design a gas analyzer (sensor analyzer module, SAM) capable of accurately detecting and autonomously monitoring critical atmospheric gases in enclosed spaces. In this Phase I effort, SRD will use its current, existing technology (miniaturized sensor platform, proprietary SMO sensor coatings and advanced signal processing algorithms) ...

    SBIR Phase I 2008 Department of DefenseSpecial Operations Command
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