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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. High-Sensitivity Monolithic Silicon CMOS APD and ROIC

    SBC: FREEDOM PHOTONICS LLC            Topic: AF14AT13

    ABSTRACT: In this effort, Freedom Photonics will develop a high-sensitivity high-resolution coherent imaging system based on a Si avalanche photodiode (APD) array and corresponding bias and read-out electronics. This will be a monolithic APD and ROIC (readout-integrated-circuit) focal plane array (FPA) system. We start from a proven high-performance CMOS electronics backplane and build the photon ...

    STTR Phase I 2015 Department of DefenseAir Force
  2. AFSCN Upgrade Based on Smart Antenna and Cognitive Satellite Radio

    SBC: INTELLIGENT FUSION TECHNOLOGY, INC.            Topic: AF14AT16

    ABSTRACT: This proposal presents an Air Force Satellite Control Network (AFSCN) upgrade scheme using smart antenna and cognitive satellite radio techniques. On the remote tracking station (RTS) side, switched beam smart antenna, distributed beam forming technique, multiple access technique based on FDMA and/or CDMA are applied to obtain multiple satellites reception objective. On the satellite si ...

    STTR Phase I 2015 Department of DefenseAir Force
  3. A Range Segment Upgrade for Air Force Satellite Control Network with Smart Antennas and Cognitive Satellite Radios

    SBC: INFOBEYOND TECHNOLOGY LLC            Topic: AF14AT16

    ABSTRACT: A range segment upgrade for Air Force satellite control network (AFSCN) will significantly improve system effectiveness via spectrum sharing and seamless interoperation. However, the upgraded system requires new capabilities such as real-time and accurate RF interference detection and mitigation, array antenna backlobe/sidelobe suppressions, accurate performance degradation prediction, ...

    STTR Phase I 2015 Department of DefenseAir Force
  4. GUARD: A Game-theoretic Universal Anti-RFI Defense framework for Satellite Communication

    SBC: INTELLIGENT FUSION TECHNOLOGY, INC.            Topic: AF14AT17

    ABSTRACT: In this proposal a Game-theoretic Universal Anti-RFI Defense (GUARD) framework for Satellite Communications is proposed. Key components of the GUARD framework include i) Radio Frequency Interferences (RFI) modeling and impact evaluation infrastructure, which allows the evaluation of the impact of RFI from various sources, and provides a comprehensive RFI knowledge base to SATCOM; ii) RF ...

    STTR Phase I 2015 Department of DefenseAir Force
  5. Phase Transitions, Nucleation and Mixing Modeling through Trans-Critical Conditions

    SBC: CASCADE TECHNOLOGIES INC            Topic: AF14AT23

    ABSTRACT: In this proposal, researchers from Cascade Technologies and Professors Matthias Ihme and Ali Mani from Stanford University lay out a plan to develop predictive modeling tools for transcritical flows. Phase I of the three phase plan is outlined in detail and extensions are proposed for Phases II and III. Central points of the Phase I plan include: A comprehensive review and assessment ...

    STTR Phase I 2015 Department of DefenseAir Force
  6. Low-Latency Embedded Vision Processor (LLEVS)

    SBC: SA PHOTONICS, LLC            Topic: AF15AT13

    ABSTRACT: Digital binocular helmet-mounted display (HMD) systems are now available that allow high resolution wide field-of-view (WFOV) digital imagery to be displayed on high resolution microdisplays. These digital HMD systems require a low-latency embedded vision processor (LLEVS) capable of implementing the necessary image processing algorithms. An SA Photonics LLEVS will be implemented on next ...

    STTR Phase I 2015 Department of DefenseAir Force
  7. Object Cueing Using Biomimetic Approaches to Visual Information Processing

    SBC: MAYACHITRA, INC.            Topic: N14AT008

    Thousands of years of evolution have produced the human vision system that computers cannot replicate well. Humans are still unsurpassed in their ability to search for objects in visual scenes. To successfully detect objects in cluttered scenes, the human brain is thought to rely on multiple factors: prior probabilities of object occurrence, global scene statistics and object co-occurrence. Machin ...

    STTR Phase II 2015 Department of DefenseNavy
  8. Mobile Health Application for Family and Behavioral Health Provider Communication

    SBC: INFERLINK CORP            Topic: A13AT018

    Clinical monitoring of mental health status has not evolved much from the routine meeting between patient and clinician, which suffers from a lack of quantification, irregular and anecdotal reporting, and does not necessarily include input from family. This is unfortunate given current technology, in which people routinely volunteer to track their own health related behavior, such as exercise and ...

    STTR Phase II 2015 Department of DefenseArmy
  9. Heterogeneous Analysis of Group Interactions and Dynamics (HAGID) for Social Media Forecasting

    SBC: PERCEPTRONICS SOLUTIONS, INC            Topic: ST12B002

    This proposal is to extend into Phase II our development of a new system for Recognition of Communities and Heterogeneous Analysis of Group Interactions and Dynamics (RC-HAGID) for Social Media Forecasting. Social media enables groups, including terroris

    STTR Phase II 2015 Department of DefenseDefense Advanced Research Projects Agency
  10. LEARNING-BASED APPROACH FOR RELEVANT DATA EXTRACTION (LARDE)

    SBC: ROBOTIC RESEARCH OPCO, LLC            Topic: N13AT016

    Robotic Research, LLC (RR) and Southwest Research Institute (SwRI) are creating a prototype Learning-based Approach for Relevant Data Extraction (LARDE). The LARDE framework is a data extraction and handling framework that can intelligently reduce the volume of raw data from on-board sensors, and organize and persistently store the reduced relevant dataset.

    STTR Phase II 2015 Department of DefenseNavy
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