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    • 2. 发明申请
    • USER-AIDED SIGNAL LINE-OF-SIGHT (LOS) MACHINE LEARNING CLASSIFIER
    • US20230003901A1
    • 2023-01-05
    • US17806110
    • 2022-06-09
    • oneNav, Inc.
    • Mahdi MaarefLionel Garin
    • G01S19/23G01S19/05G06N5/02
    • Machine learning techniques can be used to mitigate multipath in a GNSS receiver that includes a first trained model that provides extra path length (EPL) corrections in the GNSS receiver. The first trained model can be updated using an updated and trained model from one or more assistance servers that are in communication with the GNSS receiver. The GNSS receiver can provide, for a particular computed position and time, extracted features from received GNSS signals to the one or more assistance servers. The assistance servers can then use the extracted features and a source of true EPL corrections (e.g., from a 3D building map database for the particular computed position and time) to train a server model. The server model, once trained to a desired level of accuracy, can be transmitted to the GNSS receiver to replace the first trained model. The server model can be compared to the first trained model to verify it can provide more accurate EPL corrections than the first trained model. The server model and the source of true EPL corrections can be specific for a geographic region, so different regions have different server models based on the corresponding sources of true EPL corrections.