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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. Solid State High Energy Desity Batteries

    SBC: CFD RESEARCH CORPORATION            Topic: SOCOM222001

    The modern warfare environment has demonstrated an ever-increasing need for electrical power and energy carrying capacity. Soldiers are now expected to carry in excess of 20lbs of batteries for a 72-hour mission. This weight only increases when operating specialized equipment such as communication, targeting, or mobility equipment. As a consequence, lithium-ion (Li-ion) battery packs have become t ...

    SBIR Phase I 2022 Department of DefenseSpecial Operations Command
  2. Solid State High Energy Density Batteries

    SBC: BHAWIN LLC            Topic: SOCOM222001

    In Phase I project, Bhawin LLC aims to develop the current concept of solid-state Li-ion battery fabricating a single continuous phase for the anode, electrolyte, and cathode, and thus, eliminating the highly resistive interfaces between the electrolyte and electrodes found in straight solid-state Li-ion batteries. Advanced Li-ion battery technology will play a critical role in the understanding o ...

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

    SBC: QUANTUM RESEARCH INTERNATIONAL, INC.            Topic: SOCOM222002

    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
  4. 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
  5. Utilizing ML Algorithms to Track and Identify UAS Threats

    SBC: POLARIS SENSOR TECHNOLOGIES INC            Topic: SOCOM222002

    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
  6. Low SWaP Tactical Ultra-Secure Communications System

    SBC: COGNICOM INC            Topic: SOCOM221001

    The proposal is to perform a feasibility study on the creation of an ultra-secure communications system with LPD / LPI and AJ, data rates above 1 Gbps, and SWAP low enough for man portable battery powered operation. This study will look at adaption commercial LEO backhaul waveforms to be ultra-secure, using sate of the art hardware like the Xilinx RF SoC and the Dujud 3D printed conformal phased a ...

    SBIR Phase I 2022 Department of DefenseSpecial Operations Command
  7. Low SWaP Tactical Ultra-Secure Communications System

    SBC: IERUS TECHNOLOGIES INC            Topic: SOCOM221001

    When there is a contested environment, and SOCOM needs no-compromise ultra-secure communications, the IERUS Technologies Low-SWaP Ultra-Secure Tactical OTM Communication System (LUTOCS) is there. Utilizing an open agile architecture based on software defined radio (SDR) technology to implement advanced software and hardware solutions, the system is tailored for optimal performance in dynamic situa ...

    SBIR Phase I 2022 Department of DefenseSpecial Operations Command
  8. Electronic Embedded Glass

    SBC: INTELLISENSE SYSTEMS INC            Topic: SOCOM213004

    To address the USSOCOM need for a transparent in-vehicle display screen, Intellisense Systems, Inc. (Intellisense) proposes to develop a new Transparent Armor Nanostructure Display (TAND) system to enhance crew situational awareness, reduce cognitive workload, and eliminate in-vehicle stand-alone displays. This compact transparent armor (TA) display system is based on the unique combination of a f ...

    SBIR Phase I 2022 Department of DefenseSpecial Operations Command
  9. sUAS Munition Teaming for Advanced Precision Strike

    SBC: OPTO-KNOWLEDGE SYSTEMS INC            Topic: SOCOM21C001

    The US requires standoff precision strike capabilities in GPS-denied and high threat environments. This includes fire-and-forget lock-after-launch vision-based guidance for SOPGM. Due to emerging threats, a paradigm shift is occurring in the way we gather intelligence, maintain surveillance, and perform reconnaissance. ISR platforms are evolving, and artificial intelligence is at the forefront of ...

    STTR Phase I 2022 Department of DefenseSpecial Operations Command
  10. sUAS Munition Teaming for Advanced Precision Strike

    SBC: INVARIANT CORPORATION            Topic: SOCOM21C001

    This task seeks to develop advanced teaming via machine learning between small unmanned air systems and Non Line-of-Sight (NLOS) munitions in GPS denied Environments. Current precision targeting capabilities are robust to state errors from ISR targeting platforms and weapons systems seeking to passively acquire a target. Visual Based Navigation (VBN) provides required state information in GPS deni ...

    STTR Phase I 2022 Department of DefenseSpecial Operations Command
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