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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. Automating the Application of Deception Detection Heuristics to Unstructured Data

    SBC: STOTTLER HENKE ASSOCIATES, INC            Topic: N10AT029

    We propose to construct a deception detection system which will exploit scaffolding provided by a collection of largely domain-independent deception detection heuristics. These heuristics, integrated through a novel evidential reasoning system, will provide the proposed system, called Skeptic, with a significant advantage over purely inductive methods by allowing it to exploit the adversarial natu ...

    STTR Phase I 2010 Department of DefenseNavy
  2. Applications of Computational Command Leadership AI Models (ACCLAIM)

    SBC: STOTTLER HENKE ASSOCIATES, INC            Topic: ST092002

    A military without good leadership is a mob. Identification, preparation, guidance and mentoring of potential leaders are critical functions across all services. Leadership training and support can be substantially improved by refinement of theories and models on what constitutes good leadership, and what enables individual to be effective leaders. DoD needs better models of how leaders learn, ...

    STTR Phase I 2010 Department of DefenseDefense Advanced Research Projects Agency
  3. 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
  4. 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
  5. 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
  6. 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
  7. 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
  8. 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
  9. 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
  10. 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
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