Patents by Inventor Eyal Rittberg

Eyal Rittberg 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).

  • Patent number: 11181617
    Abstract: A radar sensor includes: a transmitter configured to transmit radar via a transmit antenna; a receiver configured to receive signals reflected back to the radar sensor via a receive antenna; a profile module configured to generate an energy profile including a plurality of points for a plurality of distances from the radar sensor, respectively, each of the points including an energy of the signals reflected back to the radar sensor for that one of the plurality of distances; a minimums module configured to identify ones of the plurality of points having local minimums of energy; and a curve module configured to, based on the plurality of points having local minimums of energy, generate an equation representative of a curve fit to the plurality of points having local minimums of energy, the equation relating distance from the radar sensor to baseline energy of the signals reflected back to the radar sensor.
    Type: Grant
    Filed: June 10, 2019
    Date of Patent: November 23, 2021
    Assignee: GM GLOBAL TECHNOLOGY OPERATIONS LLC
    Inventors: Eyal Rittberg, Arye Lerner
  • Patent number: 11143747
    Abstract: A system for classifying received signals from a radar system into noise or a detection includes a source of a radar energy map and a memory that stores an integral image data structure for computing an integral image. The system includes a processor in communication with the source and the memory programmed to: generate an initial image including initial cells each having an energy value based on the radar energy map; compute the integral image based on the initial image; determine a coordinate location of an initial cell; determine coordinate locations of indices associated with corners of a neighborhood surrounding the initial cell; determine an energy sum of the neighborhood based on the indices and a value of respective cells from the integral image; determine an estimated noise associated with the initial cell based on the energy sum; and determine whether the initial cell indicates the detection of an object.
    Type: Grant
    Filed: July 11, 2019
    Date of Patent: October 12, 2021
    Assignee: GM GLOBAL TECHNOLOGY OPERATIONS LLC
    Inventors: Eyal Rittberg, Boris Indelman
  • Publication number: 20210011124
    Abstract: A system for classifying received signals from a radar system into noise or a detection includes a source of a radar energy map and a memory that stores an integral image data structure for computing an integral image. The system includes a processor in communication with the source and the memory programmed to: generate an initial image including initial cells each having an energy value based on the radar energy map; compute the integral image based on the initial image; determine a coordinate location of an initial cell; determine coordinate locations of indices associated with corners of a neighborhood surrounding the initial cell; determine an energy sum of the neighborhood based on the indices and a value of respective cells from the integral image; determine an estimated noise associated with the initial cell based on the energy sum; and determine whether the initial cell indicates the detection of an object.
    Type: Application
    Filed: July 11, 2019
    Publication date: January 14, 2021
    Applicant: GM GLOBAL TECHNOLOGY OPERATIONS LLC
    Inventors: Eyal Rittberg, Boris Indelman
  • Publication number: 20200386858
    Abstract: A radar sensor includes: a transmitter configured to transmit radar via a transmit antenna; a receiver configured to receive signals reflected back to the radar sensor via a receive antenna; a profile module configured to generate an energy profile including a plurality of points for a plurality of distances from the radar sensor, respectively, each of the points including an energy of the signals reflected back to the radar sensor for that one of the plurality of distances; a minimums module configured to identify ones of the plurality of points having local minimums of energy; and a curve module configured to, based on the plurality of points having local minimums of energy, generate an equation representative of a curve fit to the plurality of points having local minimums of energy, the equation relating distance from the radar sensor to baseline energy of the signals reflected back to the radar sensor.
    Type: Application
    Filed: June 10, 2019
    Publication date: December 10, 2020
    Inventors: Eyal RITTBERG, Arye Lerner
  • Publication number: 20200278423
    Abstract: Processor-implemented methods and systems that perform target verification on a spectral response map to remove false alarm detections at the beamforming stage for sensing radars (i.e., prior to performing peak response identification) using a convolutional neural network (CNN) are provided. The processor-implemented methods include: generating a spectral response map from the radar data; and, executing the CNN to determine whether the response map represents a valid target detection and to classify the response map as a false alarm when the response map does not represent a valid target detection. Subsequent to the execution of the CNN, only response maps with valid targets are processed to generated therefrom a direction of arrival (DOA) command.
    Type: Application
    Filed: March 1, 2019
    Publication date: September 3, 2020
    Applicant: GM GLOBAL TECHNOLOGY OPERATIONS LLC
    Inventors: Eyal Rittberg, Omri Rozenzaft