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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. AAV Benchmark

    SBC: Vectraxx, Inc.            Topic: N111016

    The term benchmark originates from the chiseled horizontal marks that surveyors made, into which an angle-iron could be placed to bracket ("bench") a leveling rod, thus ensuring that the leveling rod can be repositioned in exactly the same place in the future. A benchmark in computer terms is the result of running a computer program, or a set of programs, in order to assess the relative performanc ...

    SBIR Phase II 2012 Department of DefenseNavy
  2. Accelerated Linear Algebra Solvers for Multi-Core GPU-Based Computing Architectures

    SBC: EM PHOTONICS INC            Topic: AF09BT18

    ABSTRACT: High-performance computing (HPC) programmers and domain experts, such as those in the Air Force's research divisions, develop solvers for a wide variety of application areas such as modeling next generation aircraft and weapons designs and advanced image processing analysis. When developing software for HPC systems, the programmer should not spend the majority of their time optimiz ...

    STTR Phase II 2012 Department of DefenseAir Force
  3. Accurate Scene Generation of Target Characteristics Incorporating Dynamic Atmospheric Conditions using GAIA and OCEANUS

    SBC: COMPUTATIONAL PHYSICS, INC.            Topic: MDA11001

    The Ballistic Missile Defense System"s ability to detect and track enemy missiles against space, ocean, or terrain backgrounds, including any intervening clouds as well as atmospheric turbulence, requires prior knowledge of the environmental radiance conditions to support the development of optimal airborne sensors and detection approaches. To support sensor development there is a need for an accu ...

    SBIR Phase I 2012 Department of DefenseMissile Defense Agency
  4. A Cognitive Architecture for Naval Mine Countermeasures (MCM)

    SBC: KNEXUS RESEARCH LLC            Topic: N121082

    Mine Countermeasures (MCM) missions of tomorrow will increasingly exploit autonomous vehicles such as the remote multi-mission vehicle to reduce risk to personnel and equipment. However, existing approaches are limited for continuous sensing and planning needed to deal with the dynamic and uncertain nature of the MCM missions. To address this gap we will consider alternative approaches that merge ...

    SBIR Phase I 2012 Department of DefenseNavy
  5. A Compact, Low Cost, Handheld Sensor for Non- Destructive Material Case Depth Verification

    SBC: ALPHASENSE, INC.            Topic: N102141

    In this SBIR program, AlphaSense, Inc. teamed with the Center for Non-destructive Evaluations at Iowa State University to develop a compact, low cost handheld sensor for non-destructive material case depth verification. In phase I, we have proven the feasibility of using an alternating current potential drop (ACPD) sensor for non-destructive measurements of case depth. Phase II will be focusing on ...

    SBIR Phase II 2012 Department of DefenseNavy
  6. Acoustic Signature Bundling

    SBC: PROGENY SYSTEMS, LLC            Topic: N151074

    Todays sonar operators are presented with a voluminous amount of acoustic contact data spanning a large multidimensional search space of arrays, bearings, frequencies, and time. Improvement in arrays, signal processing, and computer performance have led to the ability to detect even more contacts. When combined with high contact density and long contact hold times common at Integrated Undersea Sur ...

    SBIR Phase I 2015 Department of DefenseNavy
  7. Active Signal Processing Enhancements for Classification of Low Signal-to-Noise Ratio (SNR) Sonar Signals in Doppler Clutter

    SBC: ADAPTIVE METHODS, INC.            Topic: N151034

    The acoustic environment encountered in pulsed active sonar provides some of the most formidable challenges seen in modern signal processing. The confluence of strong bottom clutter, ownship Doppler spreading, and discrete mutual interference results in clutter leakage and sidelobes across beam and Doppler spaces. Platform motion causes clutter returns to be shifted in Doppler, leading to elevated ...

    SBIR Phase I 2015 Department of DefenseNavy
  8. Active Software Defense to Reduce Threat Capability Effectiveness

    SBC: Power Fingerprinting, Inc            Topic: OSD11IA6

    Perimeter and passive cyber defenses must be complemented with an active defense mechanism to elevate the risks, or costs, a potential attacker must face. The effectiveness of an active defense mechanism is ultimately limited by its ability to detect threats fast, accurately, and reliably. For this Phase I project, we propose to determine the feasibility of creating an active defense solution base ...

    SBIR Phase I 2012 Department of DefenseAir Force
  9. Active Vibration Control for Enhanced Satellite Communications

    SBC: FIBERTEK, INC.            Topic: AF112059

    ABSTRACT: We propose the use of adaptive algorithms for laser jitter suppression on a variety of space and airborne platforms, that are capable of closed-loop bandwidths exceeding 1kHz, residual jitter of few urads or less, and narrowband jitter suppression exceeding 20dB. For implementation, in addition to the use of conventional compact actuators, an advanced'inertia-less'actuator wil ...

    SBIR Phase I 2012 Department of DefenseAir Force
  10. Adaptable Multi-Layer Inference System for Distributed Sensor Networks

    SBC: ADAPTIVE METHODS, INC.            Topic: DTRA112002

    Adaptive Methods and Applied Research Laboratory at Penn State are developing a hierarchical inference approach for multi-modal unattended ground sensor (UGS) networks. that will enable significant performance gains via integrated machine learning techniques, to include In situ performance characterization and automated adaptation to site-specific environmental characteristics; unsupervised learni ...

    SBIR Phase I 2012 Department of DefenseDefense Threat Reduction Agency
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