Distributed automotive radar architecture

    公开(公告)号:US11368222B2

    公开(公告)日:2022-06-21

    申请号:US16689952

    申请日:2019-11-20

    Abstract: Apparatus and methods are disclosed for communicating between distributed automotive sensors, including radar sensors, wherein sensors transmit a synchronization (SYNC) signal, each SYNC signal transmitted via a substantially equal-length fiber optic link corresponding with each sensor. A central node receives the SYNC signals via the fiber optic links corresponding with each of the sensors and determines a master SYNC signal based on the received SYNC signals. The central node then transmits the master SYNC signal via the fiber optic links to the sensors, which receive the master SYNC signal and transmit, via fiber optic link, sensor data synchronized in accordance with the master SYNC signal. The synchronized sensor data are received at the central node and coherently aggregated, and transmitted to a compute node for post-processing. For radar data, the post-processing may include determination of an angular position of an object within detection range of at least two radar sensors.

    Ego-velocity estimation using radar or LIDAR beam steering

    公开(公告)号:US11914046B2

    公开(公告)日:2024-02-27

    申请号:US17107421

    申请日:2020-11-30

    CPC classification number: G01S17/931 G02B26/123 G01S7/4812

    Abstract: Methods, systems, computer-readable media, and apparatuses for radar or LIDAR measurement are presented. Some configurations include transmitting, via a transceiver, a first beam having a first frequency characteristic; calculating a distance between the transceiver and a moving object based on information from at least one reflection of the first beam; transmitting, via the transceiver, a second beam having a second frequency characteristic that is different than the first frequency characteristic, wherein the second beam is directed such that an axis of the second beam intersects a ground plane; and calculating an ego-velocity of the transceiver based on information from at least one reflection of the second beam. Applications relating to road vehicular (e.g., automobile) use are described.

    Super-resolution enhancement techniques for radar

    公开(公告)号:US11899132B2

    公开(公告)日:2024-02-13

    申请号:US17029722

    申请日:2020-09-23

    CPC classification number: G01S7/414 G01S7/417 G01S7/4873 G01S13/5244

    Abstract: Embodiments provided herein allow for identification of one or more regions of interest in a radar return signal that would be suitable for selected application of super-resolution processing. One or more super-resolution processing techniques can be applied to the identified regions of interest. The selective application of super-resolution processing techniques can reduce processing requirements and overall system delay. The output data of the super-resolution processing can be provided to a mobile computer system. The output data of the super-resolution processing can also be used to reconfigure the radar radio frequency front end to beam form the radar signal in region of the detected objects. The mobile computer system can use the output data for implementation of deep learning techniques. The deep learning techniques enable the vehicle to identify and classify detected objects for use in automated driving processes. The super-resolution processing techniques can be implemented in analog and/or digital circuitry.

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