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    Radar Device and Method of Operating a Radar Device
    1.
    发明公开
    Radar Device and Method of Operating a Radar Device 审中-公开

    公开(公告)号：US20240004055A1

    公开(公告)日：2024-01-04

    申请号：US18334013

    申请日：2023-06-13

    Applicant: Infineon Technologies AG

    Inventor： Julius Ott ,  Avik Santra ,  Lorenzo Servadei

    IPC: G01S13/58 ,  G01S7/41

    CPC classification number: G01S13/581 ,  G01S7/417

    Abstract: A radar device includes a radar front end configured to send radar signals and to receive reflected radar signals, processing circuitry configured to provide digital radar data based on the received reflected radar signals, and a digital filter configured to process the digital radar data to obtain information about objects which reflected the radar signals. The device further comprises machine learning logic with a policy network configured to set the parameters of the digital filter based on the digital radar data, and a reward value generating network including a plurality of heads, each head configured to provide a respective expected reward value for a setting of parameters by the policy network. The radar device is further configured to detect that a scene captured by the radar device is not reliably processable based on a distribution of the expected reward values generated by the plurality of heads.

    METHOD, APPARATUS AND COMPUTER PROGRAM FOR CLASSIFYING RADAR DATA FROM A SCENE, METHOD, APPARATUS AND COMPUTER PROGRAM FOR TRAINING ONE OR MORE NEURAL NETWORKS TO CLASSIFY RADAR DATA
    3.
    发明公开
    METHOD, APPARATUS AND COMPUTER PROGRAM FOR CLASSIFYING RADAR DATA FROM A SCENE, METHOD, APPARATUS AND COMPUTER PROGRAM FOR TRAINING ONE OR MORE NEURAL NETWORKS TO CLASSIFY RADAR DATA 审中-公开

    公开(公告)号：US20240255631A1

    公开(公告)日：2024-08-01

    申请号：US18407930

    申请日：2024-01-09

    Applicant: Infineon Technologies AG

    Inventor： Xiangyuan Peng ,  Souvik Hazra ,  Lorenzo Servadei

    IPC: G01S13/58 ,  G06F18/2415

    CPC classification number: G01S13/582 ,  G06F18/2415

    Abstract: In accordance with an embodiment, a method includes: obtaining radar data from a scene; determining cadence-velocity data and micro range-Doppler data from the radar data; encoding the cadence-velocity data to obtain a cadence-velocity feature vector using a first trained autoencoder and encoding the micro range-Doppler data to obtain a range-Doppler feature vector using a second trained autoencoder; decoding the cadence-velocity feature vector to obtain reconstructed cadence-velocity data using a first trained decoder and decoding the range-Doppler feature vector to obtain reconstructed range-Doppler data using a second trained decoder; determining first reconstruction loss information based on the cadence-velocity data and the reconstructed cadence-velocity data and determining second reconstruction loss information based on the micro range-Doppler data and the reconstructed range-Doppler data; and classifying the radar data based on the first reconstruction loss information and the second reconstruction loss information.

    Scene-Adaptive Radar
    4.
    发明申请
    Scene-Adaptive Radar 有权

    公开(公告)号：US20230040007A1

    公开(公告)日：2023-02-09

    申请号：US17396032

    申请日：2021-08-06

    Applicant: Infineon Technologies AG

    Inventor： Lorenzo Servadei ,  Michael Stephan ,  Avik Santra

    IPC: G06K9/00 ,  G06N3/08 ,  G06N3/04 ,  G01S13/89

    Abstract: In an embodiment, a method includes: receiving first radar data from a millimeter-wave radar sensor; receiving a set of hyperparameters with a radar processing chain; generating a first radar processing output using the radar processing chain based on the first radar data and the set of hyperparameters; updating the set of hyperparameters based on the first radar processing output using a hyperparameter selection neural network; receiving second radar data from the millimeter-wave radar sensor; and generating a second radar processing output using the radar processing chain based on the second radar data and the updated set of hyperparameters.

    TRAINING OF MACHINE-LEARNING ALGORITHM USING EXPLAINABLE ARTIFICIAL INTELLIGENCE
    6.
    发明公开
    TRAINING OF MACHINE-LEARNING ALGORITHM USING EXPLAINABLE ARTIFICIAL INTELLIGENCE 审中-公开

    公开(公告)号：US20240028962A1

    公开(公告)日：2024-01-25

    申请号：US18346532

    申请日：2023-07-03

    Applicant: Infineon Technologies AG

    Inventor： Lorenzo Servadei ,  Huawei Sun ,  Avik Santra

    IPC: G06N20/00

    CPC classification number: G06N20/00

    Abstract: In accordance with an embodiment, a method of training of a machine-learning algorithm includes: obtaining a training dataset comprising multiple training feature vectors and associated ground-truth labels, the multiple training feature vectors representing respective radar measurement datasets; determining, for each one of the multiple training feature vectors, a respective weighting factor by employing an explainable artificial-intelligence analysis of the machine-learning algorithm in a current training state; and training the machine-learning algorithm based on loss values that are determined based on a difference between respective classification predictions made by the machine-learning algorithm in the current training state for each one of the multiple training feature vectors and the ground-truth labels, wherein the loss values are weighted using the respective weighting factors associated with each training feature vector.

    People Counting Based on Radar Measurement
    7.
    发明公开
    People Counting Based on Radar Measurement 审中-公开

    公开(公告)号：US20230393240A1

    公开(公告)日：2023-12-07

    申请号：US18317749

    申请日：2023-05-15

    Applicant: Infineon Technologies AG

    Inventor： Lorenzo Servadei ,  Souvik Hazra ,  Julius Ott ,  Avik Santra ,  Huawei Sun ,  Michael Stephan

    IPC: G01S7/41 ,  G01S13/58

    CPC classification number: G01S7/417 ,  G01S13/584 ,  G01S7/415

    Abstract: In accordance with an embodiment, a method includes estimating a people count of one or more persons included in the scene based on a first range-Doppler measurement map and the second range-Doppler measurement map derived from a radar measurement dataset. Estimating the people count includes inputting the first range-Doppler measurement map into a first data processing pipeline of a neural network algorithm, and inputting the second range-Doppler measurement map into a second data processing pipeline of the neural network algorithm. The first data processing pipeline and the second data processing pipeline includes range-Doppler convolutional layers implementing two-dimensional convolutions along the range dimension and the Doppler dimension, and the neural network algorithm includes an output section for processing a combination of a first output of the first data processing pipeline and a second output of the second data processing pipeline in a regression block.

    Radar interference mitigation
    9.
    发明授权
    Radar interference mitigation 有权

    公开(公告)号：US11614511B2

    公开(公告)日：2023-03-28

    申请号：US17024306

    申请日：2020-09-17

    Applicant: Infineon Technologies AG

    Inventor： Lorenzo Servadei ,  Avik Santra

    IPC: G01S7/02 ,  G01S7/35 ,  G01S7/41 ,  G01S13/89

    Abstract: In an embodiment, a method for radar interference mitigation includes: transmitting a first plurality of radar signals having a first set of radar signal parameter values; receiving a first plurality of reflected radar signals; generating a radar image based on the first plurality of reflected radar signals; using a continuous reward function to generate a reward value based on the radar image; using a neural network to generate a second set of radar signal parameter values based on the reward value; and transmitting a second plurality of radar signals having the second set of radar signal parameter values.

    METHOD AND APPARATUS TO EVALUATE RADAR IMAGES AND RADAR DEVICE
    10.
    发明申请
    METHOD AND APPARATUS TO EVALUATE RADAR IMAGES AND RADAR DEVICE 有权

    公开(公告)号：US20220383537A1

    公开(公告)日：2022-12-01

    申请号：US17827340

    申请日：2022-05-27

    Applicant: Infineon Technologies AG

    Inventor： Lorenzo Servadei ,  Avik Santra

    IPC: G06T7/70 ,  G06T7/277 ,  G06T3/00 ,  G01S13/89

    Abstract: In an embodiment, a method to evaluate radar images includes providing a first raw radar image and a second raw radar image and determining, whether a reliability criterion is fulfilled. The method further includes using a first coordinate and a second coordinate output by a trained neural network as an estimate of a position of an object if the reliability criterion is fulfilled, the trained neural network using the first raw radar image and the second raw radar image as an input. The method further includes using a third coordinate and a fourth coordinate output by another radar processing pipeline as the estimate of the position of the object if the reliability criterion is not fulfilled, the radar processing pipeline using the first raw radar image and the second raw radar image as an input.

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