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    VELOCITY AND RANGE DISAMBIGUATION USING RADAR NETWORKS WITH WAVEFORM OPTIMIZATION
    3.
    发明公开
    VELOCITY AND RANGE DISAMBIGUATION USING RADAR NETWORKS WITH WAVEFORM OPTIMIZATION 审中-公开

    公开(公告)号：EP4506726A1

    公开(公告)日：2025-02-12

    申请号：EP23190923.5

    申请日：2023-08-10

    Applicant: GM Cruise Holdings LLC

    Inventor： SANSON, Jessica Bartholdy ,  GÜTLEIN-HOLZER, Johanna ,  BARTHELME, Andreas ,  KABAKCHIEV, Kalin Hirstov ,  GIERE, Andre

    IPC: G01S13/58 ,  G01S13/931 ,  G01S13/34 ,  G01S13/42 ,  G01S13/87

    Abstract: A radar sensor system comprises a first radar sensor and at least a second radar sensor and one or more processors configured to assign different pulse rate intervals (PRI) to the first radar sensor and the second radar sensor. The processor(s)s are further configured to: receive ambiguous velocity estimates from the first and second radar sensors, respectively; determine maximum detectable velocity (Vmax) values for the first and second radar sensors based on their respective PRIs; generate a first velocity vector for the first radar sensor based on the first Vmax and the first ambiguous velocity estimate; generate a second velocity vector for the second radar sensor based on the second Vmax and the second ambiguous velocity estimate; compare velocity values in the first and second velocity vectors; and identify and output a velocity value common to the first and second velocity vectors as a correct unambiguous velocity of the object.

    DEVICE AND COMPUTER IMPLEMENTED METHOD FOR MACHINE LEARNING, TECHNICAL SYSTEM COMPRISING THE DEVICE
    6.
    发明公开
    DEVICE AND COMPUTER IMPLEMENTED METHOD FOR MACHINE LEARNING, TECHNICAL SYSTEM COMPRISING THE DEVICE 审中-公开

    公开(公告)号：EP4492083A1

    公开(公告)日：2025-01-15

    申请号：EP23184414.3

    申请日：2023-07-10

    Applicant: Robert Bosch GmbH

    Inventor： Beluch, William Harris ,  Patel, Kanil

    IPC: G01S7/41 ,  G01S13/42 ,  G01S13/50 ,  G01S7/02 ,  G06N20/00 ,  G06N5/01 ,  G06N3/04 ,  G06N3/08

    Abstract: A device and a computer implemented method for machine learning, wherein the method comprises providing a first model (300), in particular a neural network that comprises weights, that is configured to map data (302) of a first radar spectrum, in particular data from a region of interest of the first radar spectrum, to first features (304) that represent the data (302), providing the data (302) and a physical attribute of the data, in particular a range (108), an azimuth, a velocity or an indication of the polarizations of the sent and received radar signals that the data is based on, providing a first output (306) that is configured to map the first features (304) to a prediction of the physical attribute, in particular a prediction (310) of the range, a prediction (314) of the azimuth, a prediction (316) of the velocity or a prediction (322, ..., 328) of the indication of the polarizations of the sent and received radar signals, mapping the data (302) with the first model (300) to the first features (304), mapping the first features (304) with the first output (306) to the prediction of the physical attribute, and learning the first model (300), in particular learning the weights, depending on a difference between the prediction of the physical attribute and the physical attribute. A technical system comprising the device.

    RADAR BASED THREE DIMENSIONAL POINT CLOUD FOR AUTONOMOUS VEHICLES
    8.
    发明公开
    RADAR BASED THREE DIMENSIONAL POINT CLOUD FOR AUTONOMOUS VEHICLES 审中-公开

    公开(公告)号：EP4488709A3

    公开(公告)日：2025-01-15

    申请号：EP24214132.3

    申请日：2018-12-03

    Applicant: WAYMO LLC

    Inventor： CAMPBELL, Timothy

    IPC: G01S13/931 ,  G01S13/89 ,  G01S7/35 ,  G01S13/90 ,  G01S7/03 ,  G01S13/42 ,  G01S13/44 ,  G01S13/87 ,  G01S13/93 ,  H01Q21/00 ,  G01S7/02

    Abstract: Example embodiments described herein involve determining three dimensional data representative of an environment for an autonomous vehicle using radar. An example embodiment involves receiving radar reflection signals at a radar unit coupled to a vehicle and determining an azimuth angle and a distance for surfaces in the environment causing the radar reflection signals. The embodiment further involves determining an elevation angle for the surfaces causing the radar reflection signals based on phase information of the radar reflection signals and controlling the vehicle based at least in part on the azimuth angle, the distance, and the elevation angle for the surfaces causing the plurality of radar reflection signals. In some instances, the radar unit is configured to receive radar reflection signals using a staggered linear array with one or multiple radiating elements offset in the array.

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