MULTIPATH MITIGATION IN GNSS RECEIVERS WITH MACHINE LEARNING MODELS

    公开(公告)号:US20230050047A1

    公开(公告)日:2023-02-16

    申请号:US17836116

    申请日:2022-06-09

    申请人: oneNav, Inc.

    IPC分类号: G01S19/23 G06N3/04

    摘要: Machine learning techniques are used, in one embodiment, to mitigate multipath in an L5 GNSS receiver. In one embodiment, training data is generated to provide ground truth data for excess path length (EPL) corrections for a set of received GNSS signals. A system extracts features from the set of received GNSS signals and uses the extracted features and the ground truth data to train a set of one or more neural networks that can produce EPL corrections for pseudorange measurements. The trained set of one or more neural networks can be deployed in GNSS receivers and used in the GNSS receivers to correct pseudorange measurements using EPL corrections provided by the trained set of neural networks.

    MATCHING FOR GNSS SIGNALS
    4.
    发明申请

    公开(公告)号:US20210325548A1

    公开(公告)日:2021-10-21

    申请号:US17230014

    申请日:2021-04-14

    申请人: oneNav, Inc.

    IPC分类号: G01S19/42 G01S19/40 G01S19/32

    摘要: This disclosure describes methods, systems and machine readable media that can provide position solutions using, for example, pattern matching with GNSS signals in urban canyons. In one method, based upon an approximate location in an urban canyon and a set of 3D data about building structures in the urban canyon, an expected signal reception data can be generated for both line of sight and non-line of sight GNSS signals from GNSS satellites, or other sources of GNSS signals, at each point in a set of points in a grid (or other model) in the vicinity of the approximate location). This expected signal reception data can be matched to a received set of GNSS signals that have been received by a GNSS receiver, and the result of the matching can produce an adjustment to the approximate location that is used in the position solution of the GNSS receiver.