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    VELOCITY ESTIMATION AND ANGLE OFFSET CORRECTION IN SAR IMAGES BY PERFORMING IMAGE MATCHING
    3.
    发明公开
    VELOCITY ESTIMATION AND ANGLE OFFSET CORRECTION IN SAR IMAGES BY PERFORMING IMAGE MATCHING 审中-公开

    公开(公告)号：US20240077607A1

    公开(公告)日：2024-03-07

    申请号：US17901792

    申请日：2022-09-01

    申请人： GM GLOBAL TECHNOLOGY OPERATIONS LLC

    发明人： Oded Bialer ,  Dan Levi

    IPC分类号： G01S13/90 ,  G01S13/58 ,  G01S13/931

    CPC分类号： G01S13/9029 ,  G01S13/589 ,  G01S13/931

    摘要： A method, system and vehicle that repetitively correct angle offsets in a synthetic aperture radar image of a vehicle while the vehicle is in motion by utilizing a radar system and a camera to determine accurate velocity of a measured object by matching angles of the object in the SAR image with angles of the object in the camera image, thereby reducing angle offsets of objects in the SAR image. The method includes obtaining an SAR image of another vehicle via a radar unit of the vehicle, obtaining a camera image of the other vehicle via a camera unit of the vehicle, determining an association between at least one object in the SAR image and a corresponding at least one object in the camera image, correcting a velocity estimation of the vehicle based on the determined association, and adjusting the SAR image based on the corrected velocity estimation.

    Robust reflection point detection
    6.
    发明授权
    Robust reflection point detection 有权

    公开(公告)号：US11668789B2

    公开(公告)日：2023-06-06

    申请号：US17123414

    申请日：2020-12-16

    申请人： GM GLOBAL TECHNOLOGY OPERATIONS LLC

    发明人： Oded Bialer ,  Amnon Jonas

    IPC分类号： G01S7/285 ,  G01S13/06 ,  G01S13/58 ,  G01S13/931 ,  G01S13/00

    CPC分类号： G01S7/285 ,  G01S13/06 ,  G01S13/58 ,  G01S13/931

    摘要： A radar system and method include a sparse array receive element and a processing device. The system performs a beamforming operation on a received radar signal to generate a beamforming spectrum, which contains superposed impulse responses with relative power and angle. The processing device executes an iterative detection routine, starting with a first stage detection that compares the beamforming spectrum to an active power threshold and identifies tentative detection points. In the second stage detection, the processing device determines a certain detection point with the greatest relative power and updates the active power threshold for subsequent iterations of the detection routine. The update involves centering the impulse response related to the certain detection point around its angle, multiplying the relative power by the impulse response, and summing the product with the active power threshold. This process continues until a final set of detection points is obtained.

    Azimuth and elevation radar imaging with single-dimension antenna arrays of radar system
    7.
    发明授权
    Azimuth and elevation radar imaging with single-dimension antenna arrays of radar system 有权

    公开(公告)号：US11327170B2

    公开(公告)日：2022-05-10

    申请号：US16390920

    申请日：2019-04-22

    申请人： GM Global Technology Operations LLC

    发明人： Oded Bialer ,  Amnon Jonas

    IPC分类号： G01S13/89 ,  G01S13/931 ,  G01S7/41 ,  G01S13/58 ,  G01S7/35

    摘要： A method and system involve obtaining reflected signals in a radar system using a first one-dimensional array of antenna elements and a second one-dimensional array of antenna elements. The reflected signals result from reflection of transmitted signals from the radar system by one or more objects. The method includes processing the reflected signals obtained using the first one-dimensional array of antenna elements to obtain a first array of angle of arrival likelihood values in a first plane, and processing the reflected signals obtained using the second one-dimensional array of antenna elements to obtain a second array of angle of arrival likelihood values. A four-dimensional image indicating a range, relative range rate, the first angle of arrival, and the second angle of arrival for each of the one or more objects is obtained.

    Antenna array design and processing to eliminate false detections in a radar system
    8.
    发明授权
    Antenna array design and processing to eliminate false detections in a radar system 有权

    公开(公告)号：US11262434B2

    公开(公告)日：2022-03-01

    申请号：US16371685

    申请日：2019-04-01

    申请人： GM Global Technology Operations LLC

    发明人： Amnon Jonas ,  Oded Bialer

    IPC分类号： G01S7/03 ,  G01S13/931

    摘要： A system and method to eliminate false detections in a radar system involve arranging an array of antenna elements into two or more sub-arrays with a spacing between adjacent ones of the antenna elements of one of the two or more sub-arrays being different than a spacing between adjacent ones of the antenna elements of at least one other of the two or more sub-arrays. The method includes receiving reflected signals at the two or more sub-arrays resulting from transmitting transmit signals from the antenna elements of the two or more sub-arrays, and processing the reflected signals to distinguish an actual angle from the radar system to an object that contributed to the reflected signals from ambiguous angles at which the false detections of the object are obtained. A location of the object is determined as a result of the processing.

    Deep learning for super resolution in a radar system
    9.
    发明授权
    Deep learning for super resolution in a radar system 有权

    公开(公告)号：US10976412B2

    公开(公告)日：2021-04-13

    申请号：US16264807

    申请日：2019-02-01

    申请人： GM Global Technology Operations LLC

    发明人： Yaron Eshet ,  Igal Bilik ,  Oded Bialer

    IPC分类号： G01S7/41 ,  G01S13/931

    摘要： A system and method to use deep learning for super resolution in a radar system include obtaining first-resolution time samples from reflections based on transmissions by a first-resolution radar system of multiple frequency-modulated signals. The first-resolution radar system includes multiple transmit elements and multiple receive elements. The method also includes reducing resolution of the first-resolution time samples to obtain second-resolution time samples, implementing a matched filter on the first-resolution time samples to obtain a first-resolution data cube and on the second-resolution time samples to obtain a second-resolution data cube, processing the second-resolution data cube with a neural network to obtain a third-resolution data cube, and training the neural network based on a first loss obtained by comparing the first-resolution data cube with the third-resolution data cube. The neural network is used with a second-resolution radar system to detect one or more objects.

    DEEP LEARNING FOR DE-ALIASING AND CONFIGURING A RADAR SYSTEM
    10.
    发明申请
    DEEP LEARNING FOR DE-ALIASING AND CONFIGURING A RADAR SYSTEM 审中-公开

    公开(公告)号：US20200249315A1

    公开(公告)日：2020-08-06

    申请号：US16264826

    申请日：2019-02-01

    申请人： GM Global Technology Operations LLC

    发明人： Yaron Eshet ,  Oded Bialer ,  Igal Bilik

    IPC分类号： G01S7/41 ,  G01S13/93

    摘要： Deep learning in a radar system includes obtaining unaliased time samples from a first radar system. A method includes under-sampling the un-aliased time samples to obtain aliased time samples of a first configuration, matched filtering the un-aliased time samples to obtain an un-aliased data cube and the aliased time samples to obtain an aliased data cube, and using a first neural network to obtain a de-aliased data cube. A first neural network is trained to obtain a trained first neural network. The under-sampling of the un-aliased time samples is repeated to obtain second aliased time samples of a second configuration. The method includes training a second neural network to obtain a trained second neural network, comparing results to choose a selected neural network corresponding with a selected configuration, and using the selected neural network with a second radar system that has the selected configuration to detect one or more objects.