公开(公告)号：US20240118408A1

公开(公告)日：2024-04-11

申请号：US17963311

申请日：2022-10-11

Applicant: GM GLOBAL TECHNOLOGY OPERATIONS LLC

Inventor： Oded Bialer ,  Yuval Haitman

IPC: G01S13/86 ,  G01S7/35 ,  G01S7/40 ,  G01S7/41 ,  G01S13/931

CPC classification number: G01S13/865 ,  G01S7/356 ,  G01S7/4021 ,  G01S7/417 ,  G01S13/931 ,  G01S2013/93185

Abstract: A system of controlling operation of a vehicle includes a lidar unit and a radar unit configured to obtain measured lidar datapoints and a measured radar signal, respectively. A command unit is adapted to receive the measured lidar datapoints and the measured radar signal, the command unit including a processor and tangible, non-transitory memory on which instructions are recorded. The command unit is configured to identify respective objects in the measured lidar datapoints and assign a respective radar reflection intensity to the measured lidar datapoints in the respective objects. A synthetic radar signal is generated based in part on the radar reflection intensity. The command unit is configured to obtain an enhanced radar signal by adjusting the measured radar signal based on the synthetic radar reference signal.

公开(公告)号：US20240094377A1

公开(公告)日：2024-03-21

申请号：US17947298

申请日：2022-09-19

Applicant: GM Global Technology Operations LLC

Inventor： Oded Bialer ,  Yuval Haitman ,  Dan Levi

IPC: G01S13/58 ,  G01S7/40 ,  G01S7/41 ,  G01S13/50

CPC classification number: G01S13/588 ,  G01S7/4095 ,  G01S7/417 ,  G01S13/505

Abstract: A system includes a transmitter of a radar system to transmit transmitted signals, and a receiver of the radar system to receive received signals based on reflection of one or more of the transmitted signals by one or more objects. The system also includes a processor to train a neural network with reference data obtained by simulating a higher resolution radar system than the radar system to obtain a trained neural network. The trained neural network enhances detection of the one or more objects based on obtaining and processing the received signals in a vehicle. One or more operations of the vehicle are controlled based on the detection of the one or more objects.

公开(公告)号：US20240210554A1

公开(公告)日：2024-06-27

申请号：US18086158

申请日：2022-12-21

Applicant: GM GLOBAL TECHNOLOGY OPERATIONS LLC

Inventor： Oded Bialer ,  Yuval Haitman

IPC: G01S13/931 ,  G01S7/41 ,  G01S13/58

CPC classification number: G01S13/931 ,  G01S7/417 ,  G01S13/58

Abstract: A method that includes obtaining reflective radar signals regarding a scene monitored by a radar sensor system, producing reflective-intensity (RI) data based on those signals, and generating a reflective intensity volume (RIV) based on the reflective-intensity data. The RI data contains spatially invariant spectrums. The method further includes applying a trained convolutional neural network (CNN) on the generated RIV and detecting objects in the scene based, at least in part, the applying of the trained CNN on the generated RIV.

公开(公告)号：US12270891B2

公开(公告)日：2025-04-08

申请号：US17947298

申请日：2022-09-19

Applicant: GM Global Technology Operations LLC

Inventor： Oded Bialer ,  Yuval Haitman ,  Dan Levi

IPC: G01S13/58 ,  G01S7/40 ,  G01S7/41 ,  G01S13/50

Abstract: A system includes a transmitter of a radar system to transmit transmitted signals, and a receiver of the radar system to receive received signals based on reflection of one or more of the transmitted signals by one or more objects. The system also includes a processor to train a neural network with reference data obtained by simulating a higher resolution radar system than the radar system to obtain a trained neural network. The trained neural network enhances detection of the one or more objects based on obtaining and processing the received signals in a vehicle. One or more operations of the vehicle are controlled based on the detection of the one or more objects.

公开(公告)号：US20240248174A1

公开(公告)日：2024-07-25

申请号：US18098874

申请日：2023-01-19

Applicant: GM GLOBAL TECHNOLOGY OPERATIONS LLC

Inventor： Oded Bialer ,  Yuval Haitman

IPC: G01S7/41

CPC classification number: G01S7/417 ,  G01S7/412

Abstract: A method that includes obtaining reflective radar signals regarding a scene monitored by a radar sensor system having an antenna array that is characterized by effecting a reflection-ghost offset in one or more domains, determining a reflective-intensity (RI) spectrum in three domains based on the reflective radar signals, producing a filtered RI spectrum by applying a trained convolutional neural network (CNN) to the RI spectrum by, at least in part, filtering the RI spectrum using one or more CNN kernels that incorporate the reflection-ghost offset; and detecting objects in the monitored scene based, at least in part, on the filtered RI spectrum.