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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. Autonomous Landing at Unprepared Sites for a Cargo Unmanned Air System

    SBC: SYNETICS SYSTEMS ENGINEERING CORP.            Topic: N10AT039

    A rapid prototyping simulation for the Autonomous Rotorcraft Land & Take-Off (ARLTO) system will be developed to analyze and evolve requirements for the landing and take-off of a Rotary-wing Autonomous Air Vehicle (RAAV) from unprepared terrain. The simulation is based upon the Task-Pilot-Vehicle modeling system and features a UH-60 configured with a Sliding Mode Control (SCM) inner loop closure. ...

    STTR Phase I 2010 Department of DefenseNavy
  2. Mitigation of USV Motions via Wave Sensing and Prediction

    SBC: ADVANCED SCIENTIFIC CONCEPTS, LLC            Topic: N10AT036

    Advanced Scientific Concepts, Inc. (ASC) has teamed with the Department of Ocean Engineering at The University of Rhode Island to devise a sensor suite and computer algorithm to predict ocean waves to aid autonomous boat navigation in heavy weather. The centerpiece of the sensor suite is a Lidar designed by ASC that is adapted to image the ocean at glancing angles. It’s ability to acquire a 3D s ...

    STTR Phase I 2010 Department of DefenseNavy
  3. Complex Event Detection in Video and Communications

    SBC: SOAR TECHNOLOGY, LLC            Topic: N10AT040

    We will demonstrate the feasibility of detecting tactically meaningful complex events in sensor input streams using an efficient pattern matching technology embodied in the Soar cognitive architecture. Our focus in Phase I will be on video streams, such as those that might be produced by unattended ground sensors or unmanned aerial systems. To reduce risk, we propose devoting a portion of our effo ...

    STTR Phase I 2010 Department of DefenseNavy
  4. Random Number Generation for High Performance Computing

    SBC: FRONTIER TECHNOLOGY INC.            Topic: A10AT012

    Frontier Technology, Inc. and University of Rhode Island Physics department propose to develop innovative, scalable random number generators for use on multiple parallel computing architectures. Our Phase I effort will include a comprehensive assessment of currently available algorithms for parallel random number generation as well as the currently available tests designed to uncover statistical d ...

    STTR Phase I 2010 Department of DefenseArmy
  5. Adaptive Learning for Stall Pre-cursor Identification and General Impending Failure Prediction

    SBC: FRONTIER TECHNOLOGY INC.            Topic: N10AT008

    Frontier Technology, Inc. (FTI) and Northeastern University propose to investigate and develop an innovative approach to predict stall events of aircraft engines prior to occurrence and in sufficient time to allow the FADEC controller to adjust engine variables. The team will utilize vector quantization and neural network techniques to develop accurate models of engine behavior that will be used t ...

    STTR Phase I 2010 Department of DefenseNavy
  6. High Efficiency Gain Media for Eye-Safer 1.55 µm Ultrafast Fiber Amplifiers

    SBC: KAPTEYN-MURNANE LABORATORIES, INC            Topic: N10AT012

    We propose to design a high average power Er:Fiber ultrafast laser system which is pumped at 14xxnm, and at the same time solve other problems related to ultrashort pulses in fiber lasers. The advantage of using 14xxnm pumping is the reduction of the standard quantum defect from 37% to 5%, thus greatly reducing the thermal load on the system, which makes it inherently more efficient. We also inten ...

    STTR Phase I 2010 Department of DefenseNavy
  7. Instrumentation for Nanoscale Spectroscopy

    SBC: R H K TECHNOLOGY, INC.            Topic: AF08BT30

    This STTR will provide a prototype Electronics Package that integrates disparate streams of spectrographic and topographic data to provide high resolution imaging and chemical specificity at the nanoscale. It will enable development of a commercial instrument delivering routine near-field tip-enhanced optical imaging with spatial resolutions in the range of 10-50nm along with topographic (Atomic F ...

    STTR Phase I 2010 Department of DefenseAir Force
  8. Advanced Real Time Battery Monitoring and Management System

    SBC: TECHNOLOGY SERVICE CORP            Topic: N10AT013

    TSC and Purdue University will demonstrate a lab prototype of software and hardware capable of doing high speed monitoring of a Lithium-Ion cell. This monitoring needs to be specifically designed to predict failures. When a predictive failure is indicated a defensive countermeasure needs to be implemented. Our specific project goals are to: 1) Select a Lithium-Ion battery that consists of multiple ...

    STTR Phase I 2010 Department of DefenseNavy
  9. Chip-Scale Photonics for Wide Temperature and High-Speed Optical Interconnects

    SBC: ULTRA COMMUNICATIONS, INC.            Topic: A12aT008

    This program will create 40 Gbps VCSEL-based micro-transceiver (uTRX) components that operate reliably over the standard military temperature range of -55°C to 125°C in Army environments. uTRXs are low-cost, compact components that can be assembled into the PCB in close proximity to high-performance ASICs using conventional solder-reflow"pick-and-place"assembly. The small PCB footprint and sol ...

    STTR Phase I 2013 Department of DefenseArmy
  10. Inferring Social and Psychological Meaning in Social Media

    SBC: SECURBORATION, INC.            Topic: A12aT009

    The rapid ascent and adoption of social media as the dominant form of communication has led to significant analysis challenges. In particular, there is a gap in theoretically informed methods to analyze data mined and collected from social media. One primary cause of this gap is the lack of fusing structural sources of information (e.g. social network topology) with non-structural sources (message ...

    STTR Phase I 2013 Department of DefenseArmy
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