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Award Data

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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 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 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. Utilizing ML Algorithms to Track and Identify UAS Threats


    The objective of this feasibility study is to assess the concept of using LiDAR to detect, track, and identify sUAS threats assisted by Artificial Intelligence (AI) agents. Inherent in this objective is concept development and feasibility assessment of Machine Learning (ML) and AI algorithms for creation and use of LiDAR target profiles for sUAS surveillance and identification. This objective will ...

    SBIR Phase I 2022 Department of DefenseSpecial Operations Command
  2. Utilizing ML Algorithms to Track and Identify UAS Threats

    SBC: CENITH INNOVATIONS LLC            Topic: SOCOM222002

    Special Operations Command is responsible for many of our nation's most critical, no-fail missions, yet the rapid rise of Unmanned Aerial Systems (UAS) is forcing rapid adaptation in the ways these forces can detect, track, and characterize these threats. Our vision is to explore the art of the possible, pairing portable commercial LiDAR sensors with Computer Vision and Deep Learning algorithms to ...

    SBIR Phase I 2022 Department of DefenseSpecial Operations Command
  3. Utilizing ML Algorithms to Track and Identify UAS Threats


    Frequency-modulated continuous wave (FMCW) lidar is the optimal solution for cost-appropriate ground-based imaging and discrimination of small UAS at the 3 km range. In this effort Polaris will first design and assess various FMCW lidar system configurations for SOCOM’s use case. Second, Polaris will employ an innovative approach to machine learning (ML) in which innovative techniques which offe ...

    SBIR Phase I 2022 Department of DefenseSpecial Operations Command
  4. Unmanned Autonomous Vehicle Intelligence, Surveillance, and Reconnaissance (ISR) Payload Interface Master Module, PIMM

    SBC: VIPMobile, Inc.            Topic: SOCOM05005

    Significant advances have been made in sensor development, unmanned air platforms, and electronics system performance. However SOF tactical teams often do not receive near real time imagery intelligence and other sensor data relating to their area of operations. The objective of this project is to design and prove the feasibility of building a light weight, rugged, and low cost payload interface ...

    SBIR Phase I 2005 Department of DefenseSpecial Operations Command
  5. Universal Active Noise Patch Cancellation

    SBC: Physical Optics Corporation            Topic: SOCOM09005

    To address the SOCOM need for an active noise cancellation system for thrust motor controllers, Physical Optics Corporation (POC) proposes to develop a new Universal Active Noise Patch Cancellation (UANPAC) system based on a multifold active reduction patch (MARP) as a smart-skin-type acoustic actuator and an adaptive time-varying controller (ATVC) as a real-time adaptive ANC controller. The UANP ...

    SBIR Phase I 2009 Department of DefenseSpecial Operations Command
  6. Uncooled Imaging Spectrometer for Plume detection

    SBC: OPTO-KNOWLEDGE SYSTEMS INC            Topic: CBD09108

    Based on the CONOPS for gas plume detection, and the performance constraints of uncooled cameras, we propose to develop a dispersive scanning spectrometer, based on OKSI’s HyperScan and HyperSWIR family of scanning sensors. Not all uncooled cameras are equal, and not all exhibit the required characteristics for operating in spectral imaging systems under low flux environment. OKSI proposes to ...

    SBIR Phase I 2009 Department of DefenseOffice for Chemical and Biological Defense
  7. Ultra Low Latency Burst-Mode Digital Imaging System

    SBC: Silicon Micro Display, Inc.            Topic: SOCOM15003

    A burst-mode optical sensor to display architecture that allows for dynamic control over the system latency is proposed. The overall system latency of current digital imaging systems are determined and limited by the utilized video interconnection standards and the frame rates of optical sensor, image processor, and displays. In order to reduce the global system latency, an overhaul of image extra ...

    SBIR Phase I 2015 Department of DefenseSpecial Operations Command
  8. Ultrafast Gas Curtain and Wire-Reinforced X-Ray Window Debris Shields


    Alameda Applied Sciences Corporation (AASC) proposes to develop two components of a three-component, survivable debris shield for large area test exposures to cold (1-5keV) x-rays. These elements also have commercial potential in accelerators and in radiography. The elements are: an ultrafast gas curtain designed to be located close to the x-ray source to deflect plasma debris as well as ~um siz ...

    SBIR Phase I 1998 Department of DefenseNational Geospatial-Intelligence Agency
  9. 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
  10. 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
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