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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. Advanced Design Tools for Freeform Optics

    SBC: OPTICAL RESEARCH ASSOCIATES            Topic: MDA04T007

    Advanced optical systems play a pivotal role in military applications of interest to the Missile Defense Agency including advanced optical telescopes and imaging LADARs. Optics provides the eyes for surveillance, target detection and tracking. Therefore, improvements in optical design and fabrication are important targets for research and development. One significant improvement is the inclusio ...

    STTR Phase I 2004 Department of DefenseMissile Defense Agency
  2. Advanced Encryption Techniques for the Prevention of Reverse Engineering of the Programming Code in Military and Space Custom ICs and FPGAs

    SBC: MICROELECTRONICS RESEARCH DEVELOPMENT CORPORATION            Topic: MDA06T008

    We propose the development of advanced encryption techniques to make integrated circuits more secure against unauthorized intrusion, specifically the use of innovative embedded techniques to make reprogramming of high performance deep sub-micron or nano-scale FPGA or custom ASIC systems by other than the intended recipient essentially impossible. The specific concerns addressed in this proposal r ...

    STTR Phase I 2006 Department of DefenseMissile Defense Agency
  3. Advanced Passive and Active Sensors for Discrimination Seekers

    SBC: NU-TREK, INC.            Topic: MDA08T004

    Raytheon Vision Systems (RVS) is developing a next generation, high-performance large-format HgCdTe FPAs for dual-band LWIR detection for the MKV Program. Increasing the format size of dual-band long-wavelength FPAs and tailoring the detector design for specific long-wavelength bands enables seekers to be designed for larger fields-of-view, longer target acquisition ranges, and improved accuracy ...

    STTR Phase I 2009 Department of DefenseMissile Defense Agency
  4. Advanced Passive and Active Sensors for Discrimination Seekers

    SBC: SA PHOTONICS, LLC            Topic: MDA07T003

    Effective future ballistic missile defense systems will be forced to discriminate between targets and decoys. To meet this requirement, ballistic missile interceptors must contain sensors which have imaging capability. SA Photonics is proposing a program to develop a pumped laser optical source for LIDAR-RADAR imaging applications specifically targeted for ballistic missile applications. The SA ...

    STTR Phase I 2007 Department of DefenseMissile Defense Agency
  5. Advanced Radar Data Fusion

    SBC: Technology Service Corporation            Topic: MDA06T003

    The TSC team proposes to develop a new generalized Space-Time Adaptive Processing (Generalized STAP) algorithm that discriminates among classes of scatterers. The new generalized formalism is applied to the problem of 3D ISAR imaging of the reentry vehicle (RV) or another object in the ballistic missile threat complex that suppresses radar dipole clutter, using multiple ground-based radars operat ...

    STTR Phase I 2006 Department of DefenseMissile Defense Agency
  6. Advanced Sensor Data Fusion

    SBC: Frontier Technology Inc.            Topic: MDA07T004

    Frontier Technology, Inc. (FTI) and its research partner, University of Florida (UF), propose to develop designs for innovative discrimination algorithms for fusion of sensor (feature) and contextual information, to provide enhanced acquisition, tracking, and discrimination of threat objects in a cluttered multi-target environment. We propose to analyze the performance of the envisioned technology ...

    STTR Phase I 2007 Department of DefenseMissile Defense Agency
  7. Advanced Sensor Data Fusion

    SBC: Technology Service Corporation            Topic: MDA07T004

    Technology Service Corporation (TSC) and the University of Connecticut (UCONN) will develop a birth-to-death tracking concept that utilizes rotational information to improve track handover between: 1) forward-based radars, 2) mid-course ballistic missile defense tracking radars, and 3) the IR sensor on the kill vehicle. The proliferation of anti-simulation countermeasures has necessitated a multi ...

    STTR Phase I 2007 Department of DefenseMissile Defense Agency
  8. AI/ML Aided Aviation Sensors for Cognitive and Decision Optimization

    SBC: KRTKL INC.            Topic: SOCOM23B001

    krtkl (“critical”) will conduct a Phase I Feasibility Study to identify the best approach for reducing aviator cognitive load by optimizing information delivery and decision-making based on a thorough analysis of existing platforms, sensors, data sources, and onboard compute resources. This information will be used to identify Artificial Intelligence and Machine Learning based algorithms for p ...

    STTR Phase I 2023 Department of DefenseSpecial Operations Command
  9. Algorithm Performance Evaluation with Low Sample Size

    SBC: SIGNATURE RESEARCH, INC.            Topic: NGA20C001

    The team of Signature Research, Inc. and Michigan Technological University will develop and demonstrate methods and metrics to evaluate the performance of machine learning-based computer vision algorithms with low numbers of samples of labeled EO imagery. We will use the existing xView panchromatic dataset to demonstrate a proof-of-concept set of tools. If successful, in Phase II, we will extend t ...

    STTR Phase I 2021 Department of DefenseNational Geospatial-Intelligence Agency
  10. Algorithms for Look-down Infrared Target Exploitation

    SBC: SIGNATURE RESEARCH, INC.            Topic: 1

    Signature Research, Inc. (SGR) and Michigan Technological University (MTU) propose a Phase I STTR effort to develop a learning algorithm which exploits the spatio-spectral characteristics inherent within IR imagery and motion imagery.Our archive of modelled and labeled data sets will allow our team to thoroughly capture the variable elements that will drive machine learning performance.The overall ...

    STTR Phase I 2018 Department of DefenseNational Geospatial-Intelligence Agency
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