INVERSE RADAR SENSOR MODEL AND EVIDENTIAL GRID MAPPING PROCESSORS

    公开(公告)号:US20240272297A1

    公开(公告)日:2024-08-15

    申请号:US18644510

    申请日:2024-04-24

    CPC classification number: G01S13/931 G01S13/726 G01S2013/93274

    Abstract: An example device includes motion sensing and processing circuitry to generate compensated motion data for a first time based on raw motion data and a set of motion indicators including a velocity indicator for the device calculated based on the raw motion data; a radar sensor to receive reflections indicating detections and generate data points for the first time representing the detections, in which each data point includes position and velocity information of a corresponding detection relative to the radar sensor; a first circuit to generate object data for the first time based on the set of the data points and the compensated motion data for the first time; and a second circuit to calculate, based on the object data for the first time and a characteristic of the radar sensor, for each cell in a grid representing an FOV of the radar sensor at the first time, probabilities of the cell being in a free state, a stationary state, and a dynamic state.

    INVERSE RADAR SENSOR MODEL AND EVIDENTIAL GRID MAPPING PROCESSORS

    公开(公告)号:US20230089552A1

    公开(公告)日:2023-03-23

    申请号:US17472809

    申请日:2021-09-13

    Abstract: An apparatus includes an inverse radar sensor model processor and a grid mapping processor. The inverse radar sensor model processor receives radar sensor data for a time k from a radar sensor, generates object data based on the radar sensor data, and calculates instantaneous masses at the time k for each cell in a field of view (FOV) of the radar sensor based on the object data and a sensor characteristic. The inverse radar sensor model processor outputs the calculated instantaneous masses to the grid mapping processor, which also receives accumulated masses for each cell in the FOV for a time period 0:k - 1. An accumulated mass represents a combination of instantaneous masses for the cell at each time increment in the time period 0:k - 1. The grid mapping processor generates updated accumulated masses for a time period 0:k.

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