Patents by Inventor Ernest Stickels

Ernest Stickels has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Publication number: 20070268182
    Abstract: A real-time signal processing engine robustly detects, localizes, tracks and classifies ground targets based on radar signals from a multistatic radar system. The system differentiates between different targets based on an optimized cost function, which can include the total returned normalized pulse energy. The local transmitters/receivers can communicate with each other via the transmitted radar signals.
    Type: Application
    Filed: February 26, 2007
    Publication date: November 22, 2007
    Applicant: BBN Technologies Corp.
    Inventors: John Bourdelais, Ernest Stickels, William Ray Wright, David Norris, Michael Tiberio, Gary Butler
  • Publication number: 20060238407
    Abstract: A real-time signal processing engine robustly detects, localizes, tracks and classifies ground targets based on radar signals from a multistatic radar system. The system differentiates between different targets based on an optimized cost function, which can include the total returned normalized pulse energy. The local transmitters/receivers can communicate with each other via the transmitted radar signals.
    Type: Application
    Filed: April 22, 2005
    Publication date: October 26, 2006
    Inventors: John Bourdelais, Ernest Stickels, William Wright, David Norris, Michael Tiberio, Gary Butler
  • Publication number: 20050049983
    Abstract: Genetically adaptive neural network systems and methods provide environmentally adaptable classification algorithms for use, among other things, in multi-static active sonar classification. Classification training occurs in-situ with data acquired at the onset of data collection to improve the classification of sonar energy detections in difficult littoral environments. Accordingly, in-situ training sets are developed while the training process is supervised and refined. Candidate weights vectors evolve through genetic-based search procedures, and the fitness of candidate weight vectors is evaluated. Feature vectors of interest may be classified using multiple neural networks and statistical averaging techniques to provide accurate and reliable signal classification.
    Type: Application
    Filed: August 29, 2003
    Publication date: March 3, 2005
    Inventors: Gary Butler, Andrew Coon, Robert Kanyuck, Ernest Stickels