You are here

Award Data

For best search results, use the search terms first and then apply the filters
Reset

The Award database is continually updated throughout the year. As a result, data for FY20 is not expected to be complete until September, 2021.

Displaying 1 - 10 of 6398 results
  1. EROSION RESISTANT HYBRIDSIL ICEPHOBIC COATINGS FOR AIRCRAFT PROPULSION TURBOMACHINERY INLET COMPONENTS

    SBC: Nanosonic Inc.            Topic: N182115

    Through the proposed Navy SBIR program, NanoSonic will molecularly engineer and empirically optimize its HybridSil Icephobic coating technology for imparting long-term passive ice protection to aircraft propulsion turbomachinery inlet components. Unlike competing icephobic coating technologies that rely on unreacted, surface enriching / lubricating oils that impart temporary ice protection, NanoSo ...

    SBIR Phase I 2019 Department of DefenseNavy
  2. Multifunction-Multimodal Airborne Radar in Maritime/Littoral Environments

    SBC: Azure Summit Technology, Inc.            Topic: N182120

    Airborne surveillance radars continue to advance towards more flexible architectures that enable them to address evolving adversary tactics facilitated by global proliferation of RF and High Performance Embedded Computing (HPEC) technologies. Aided by these technologies, the adversary can use multiple electronic counter measures that can confuse traditional monostatic radars and obscure the true o ...

    SBIR Phase I 2019 Department of DefenseNavy
  3. Multifunction-Multimodal

    SBC: SYSTEMS & TECHNOLOGY RESEARCH LLC            Topic: N182120

    Systems & Technology Research (STR) proposes the development of a novel multifunction/multimodal airborne radar architecture leveraging STRs extensive experience in the development of software, hardware, and advanced algorithms for a wide variety of airborne radar applications. On this program, we will focus on the development of a fundamentally new airborne radar architecture that optimizes airbo ...

    SBIR Phase I 2019 Department of DefenseNavy
  4. Effect of Surface Finish and Post-Processing on the Fatigue Life of Additively Manufacturing Parts

    SBC: TECHNICAL DATA ANALYSIS, INC.            Topic: N182126

    Additive manufacturing technology is becoming more popular for the fabrication of 3D metal products as it offers rapid prototyping and large design freedom. However, with more complex geometric features due to topology optimization, it becomes infeasible to carry out traditional surface machining process to improve surface roughness for fatigue performance. In this effort, we will develop a novel ...

    SBIR Phase I 2019 Department of DefenseNavy
  5. Effect of Surface Finish and Post-Processing on the Fatigue Life of Additively Manufacturing Parts

    SBC: Triton Systems, Inc.            Topic: N182126

    Triton will develop a surface finishing process that can efficiently post-process additively manufactured metallic components to a consistent finish while enhancing material properties and part performance. Naval materials of interest include titanium, aluminum, nickel, aluminum, bronze, and stainless steel alloys.

    SBIR Phase I 2019 Department of DefenseNavy
  6. Fooling Computer Vision Classifiers with Adversarial Examples

    SBC: Triton Systems, Inc.            Topic: N182127

    Triton Systems Inc. propose to create adversarial image techniques that will both fool U.S. classifiers and can applied in operationally relevant physical modification kits to military objects. We will develop a rapid process to generate adversarial images, translate them into physical modification kits and demonstrate a reliable system to camouflage the target object independent of classifier loc ...

    SBIR Phase I 2019 Department of DefenseNavy
  7. Computer Learning Obfuscating Adversarial Kit (CLOAK)

    SBC: DECISIVE ANALYTICS CORPORATION            Topic: N182127

    In 2013, Szegedy et al. identified a series of intriguing properties of neural networks. One property introduced in the paper, adversarial examples, describes the possibility of instability in neural network classification when a small perturbation is added to input. Specifically, the authors found that a small strategic perturbation to an input image could cause a classifier to misclassify an obj ...

    SBIR Phase I 2019 Department of DefenseNavy
  8. Stackable, high voltage Silicon Carbide based DSRDs

    SBC: GENESIC SEMICONDUCTOR INC.            Topic: N182130

    Silicon carbide (SiC) based stackable drift step recovery diodes (DSRDs) with 20 kV/1 kA/=1 MHz capability are proposed in this program for potential use in the next-generation of high-power microwave pulse generators of interest to a wide range of commercial and military applications, ranging from ultra-wide band telecommunication systems, short-range local positioning systems, power lasers, grou ...

    SBIR Phase I 2019 Department of DefenseNavy
  9. Submarine Sensor Environmental Inference

    SBC: Triton Systems, Inc.            Topic: N182135

    Triton Systems proposes to develop environmental inference capabilities to provide in situ characterizations of the speed and attenuation of sound in the seabed and water column to enhance the tactical decisions and warfighting posture of submarines so informed.

    SBIR Phase I 2019 Department of DefenseNavy
  10. Compact Low Noise Acoustic Sensors for Sonobuoys

    SBC: MSI Transducers Corp.            Topic: N182136

    Through this effort, the team of MSI Transducers and QorTek will develop a compact, low-cost, low-noise acoustic sensor for sonobuoys. The MSI concept fully utilizes its expertise in the design, development, and fabrication of transducers, combined with QorTeks expertise in power electronics, underwater amplifiers and next generation piezoelectric materials, to develop a compact low-noise system.

    SBIR Phase I 2019 Department of DefenseNavy
US Flag An Official Website of the United States Government