SYSTEM AND METHOD FOR DIAGNOSING SENSOR PERFORMANCE OF AN ULTRA WIDE BAND SENSOR LOCALIZATION

    公开(公告)号:US20240172164A1

    公开(公告)日:2024-05-23

    申请号:US18049902

    申请日:2022-10-26

    CPC classification number: H04W64/00 H04B1/69

    Abstract: Systems and methods for diagnosing sensor performance of a UWB sensor localization are provided. The system comprises a UWB tag, at least four UWB anchors, and a gateway. The gateway comprises an ECU arranged to receive sensor signals from the UWB anchors. The ECU comprises a preprocessing module arranged to align the sensor signals defining aligned data and is arranged to determine intersections of the aligned data defining points of intersections. The system further comprises a clustering module arranged to cluster the points of intersections defining at least one cluster of points of the UWB anchors to calculate a clustering quality and a clustering variance of each of the at least one cluster. The ECU is arranged to find a clustering contribution of each anchor defining a first contribution low of one of the anchors and is arranged to determine an erratic anchor based the first contribution low.

    System and method of resilient ultra wide band target localization for a vehicle

    公开(公告)号:US12156097B2

    公开(公告)日:2024-11-26

    申请号:US18049891

    申请日:2022-10-26

    Abstract: A method and system of resilient UWB target localization for a vehicle are provided. The system comprises a UWB tag arranged to be mobile and trackable by way of a sensor signal and at least three UWB anchors. Each anchor is in communication with the tag. The system further comprises a gateway in communication with the anchors. The gateway comprises an ECU arranged to receive sensor signals from UWB anchors. The ECU comprises a preprocessing module, a clustering module, and a Bayesian module. The preprocessing module is arranged to align sensor signals at an aligned timestamp to define aligned data. The clustering module is arranged to cluster points of intersections, defining a sensed location for each cluster. The Bayesian module is arranged to determine a real-time location of the tag based on a Bayesian probability function to match the sensed location with a predicted location of the tag.

    SYSTEM AND METHOD FOR DIAGNOSING SENSOR PERFORMANCE OF AN ULTRA WIDE BAND SENSOR LOCALIZATION

    公开(公告)号:US20240151805A1

    公开(公告)日:2024-05-09

    申请号:US18049911

    申请日:2022-10-26

    CPC classification number: G01S5/021 G01S5/10 H04B1/7163

    Abstract: Systems and methods of diagnosing sensor performance of an ultra wide band (UWB) sensor localization for a vehicle are provided. The method comprises receiving sensor signals from at least four UWB anchors and a UWB tag for a time period. The sensor signals represent anchor coordinates and real-time distances between the tag and each anchor. The method comprises aligning the sensor signals to define aligned data. The method comprises calculating a predicted location of the UWB tag based on the aligned data and a least square of error to define a first constructed matrix and a second constructed matrix. The method comprises determining a local error of each of the at least four UWB anchors based on the least square of error and comparing each local error with an error threshold to define a first threshold high. The method comprises determining an erratic anchor based on the first threshold high.

    UWB-BASED IN-VEHICLE 3D LOCALIZATION OF MOBILE DEVICES

    公开(公告)号:US20250155541A1

    公开(公告)日:2025-05-15

    申请号:US18508579

    申请日:2023-11-14

    Abstract: A method for in-vehicle localization of a mobile device includes receiving, in real time, sensor data from a plurality of UWB sensors inside a vehicle. The plurality of UWB sensors includes a plurality of UWB anchors and a UWB tag, which is part of the mobile device. The method further includes determining a plurality of location candidates of the UWB tag based on the sensor data received, determining a plurality of sensed current locations of the UWB tag and a plurality of probabilities for each of the plurality of sensed current locations of the UWB tag using a Gaussian Kernel Density Estimation (KDE), tracking a motion of the UWB tag, and determining a real-time position of the UWB tag using a Bayesian estimation.

    System and method for diagnosing sensor performance of an ultra wide band sensor localization

    公开(公告)号:US12294970B2

    公开(公告)日:2025-05-06

    申请号:US18049902

    申请日:2022-10-26

    Abstract: Systems and methods for diagnosing sensor performance of a UWB sensor localization are provided. The system comprises a UWB tag, at least four UWB anchors, and a gateway. The gateway comprises an ECU arranged to receive sensor signals from the UWB anchors. The ECU comprises a preprocessing module arranged to align the sensor signals defining aligned data and is arranged to determine intersections of the aligned data defining points of intersections. The system further comprises a clustering module arranged to cluster the points of intersections defining at least one cluster of points of the UWB anchors to calculate a clustering quality and a clustering variance of each of the at least one cluster. The ECU is arranged to find a clustering contribution of each anchor defining a first contribution low of one of the anchors and is arranged to determine an erratic anchor based the first contribution low.

    SYSTEM AND METHOD OF RESILIENT ULTRA WIDE BAND TARGET LOCALIZATION FOR A VEHICLE

    公开(公告)号:US20240171939A1

    公开(公告)日:2024-05-23

    申请号:US18049891

    申请日:2022-10-26

    CPC classification number: H04W4/027 H04W4/40 H04W64/006

    Abstract: A method and system of resilient UWB target localization for a vehicle are provided. The system comprises a UWB tag arranged to be mobile and trackable by way of a sensor signal and at least three UWB anchors. Each anchor is in communication with the tag. The system further comprises a gateway in communication with the anchors. The gateway comprises an ECU arranged to receive sensor signals from UWB anchors. The ECU comprises a preprocessing module, a clustering module, and a Bayesian module. The preprocessing module is arranged to align sensor signals at an aligned timestamp to define aligned data. The clustering module is arranged to cluster points of intersections, defining a sensed location for each cluster. The Bayesian module is arranged to determine a real-time location of the tag based on a Bayesian probability function to match the sensed location with a predicted location of the tag.

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