Linear prediction-based bistatic detector for automotive radar

    公开(公告)号:US11774548B2

    公开(公告)日:2023-10-03

    申请号:US17242175

    申请日:2021-04-27

    CPC classification number: G01S7/021 G01S13/588 G01S13/931

    Abstract: The disclosure provides systems, apparatuses, and techniques for operating automotive MIMO radars in crowded multi-path environments to obtain reliable detections by linearly predicting whether a bistatic condition occurred. To avoid saturating computing resources processing bistatic detections, the described techniques enable a radar system to quickly identify and discard from the field-of-view radar detections that are likely a result of bistatic conditions. By ignoring unusable radar returns that are likely a result of bistatic conditions, an example radar system can focus on processing radar returns from static conditions, for example, in providing radar-based detections as output to an automotive system that is driving a vehicle in an autonomous or a semi-autonomous mode. In so doing, the example radar system provides a highly accurate static object detector that is sufficiently quick in detecting bistatic conditions for use in vehicle-safety systems as well as autonomous and semi-autonomous control.

    Radar System with Sequential Two-Dimensional Angle Estimation

    公开(公告)号:US20230228845A1

    公开(公告)日:2023-07-20

    申请号:US17652625

    申请日:2022-02-25

    CPC classification number: G01S7/4021 G01S13/42 G01S13/931 G01S13/878 H01Q21/08

    Abstract: This document describes techniques and systems of a radar system with sequential two-dimensional (2D) angle estimation. The radar system can efficiently estimate angles in two dimensions for detections. For example, a radar system includes a processor and an antenna that can receive electromagnetic energy reflected by one or more objects. The antenna includes a 2D array that includes antenna elements positioned in a first dimension and a second dimension. The processor can determine, using electromagnetic energy received by the 2D array, first angles in the first dimension associated with a detection of the one or more objects. The processor can then steer the 2D array to the first angle to generate a steered 1D array for each first angle. Using the steered 1D array, the processor can determine second angles associated with the first angle for the detection.

    Radar system with modified orthogonal linear antenna subarrays

    公开(公告)号:US11619705B2

    公开(公告)日:2023-04-04

    申请号:US17075632

    申请日:2020-10-20

    Abstract: This document describes techniques and systems of a radar system with modified orthogonal linear antenna subarrays and an angle-finding module. The described radar system includes a first one-dimensional (1D) (e.g., linear) subarray; a second 1D subarray positioned orthogonal to the first 1D subarray; and a two-dimensional (2D) subarray. Using electromagnetic energy received by the first 1D subarray and the second 2D subarray, azimuth angles and elevation angles associated with one or more objects can be determined. The radar system associates, using electromagnetic energy received by the 2D subarray, pairs of an azimuth angle and an elevation angle to the respective objects. In this way, the described systems and techniques can reduce the number of antenna elements while maintaining the angular resolution of a rectangular 2D array with similar aperture sizing.

    Radar System to Detect Angles in Bistatic and Monostatic Scenarios

    公开(公告)号:US20220244370A1

    公开(公告)日:2022-08-04

    申请号:US17318621

    申请日:2021-05-12

    Abstract: This document describes techniques and systems to enable a radar system to detect angles in bistatic and monostatic scenarios. In some examples, an automotive radar system includes one or more processors. The processors can obtain electromagnetic (EM) energy reflected by objects and generate, based on the reflected EM energy, a two-dimensional (2D) data matrix. The 2D data matrix has a number of rows corresponding to the number of antenna elements in a transmitter array and a number of columns corresponding to the number of antenna elements in a receiver array. Using the 2D data matrix, the processors can determine DoA estimates and DoD estimates in monostatic and bistatic scenarios. By comparing the DoA estimates to the DoD estimates, the processors can determine an angle associated with the objects. In this way, the described techniques and systems can enable angle detection in monostatic and bistatic conditions with improved angular resolution and reduced cost.

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