Systems and methods of determining an improved user location using real world map and sensor data

    公开(公告)号:US12000939B2

    公开(公告)日:2024-06-04

    申请号:US16340587

    申请日:2017-03-20

    Applicant: Google LLC

    CPC classification number: G01S19/50 G01C21/206 G01S5/0269

    Abstract: Systems and methods for determining an improved user location using real world map data and/or sensor data are provided. In one embodiment, the method can include obtaining an initial estimate of a location of a user device and maps information corresponding to a geographic area at least partially surrounding the initial estimate of the location of the user device. The maps information can include one or more physical boundaries located at least in part within the geographic area at least partially surrounding the initial estimate. The method can further include determining a set of permissible areas that can potentially include the user device. The set of permissible areas can be determined based at least in part on the one or more physical boundaries. The method can further include revising the initial estimate to provide a revised estimate for the location of the user device based at least in part on the set of permissible areas.

    GENERATING WIRELESS NETWORK ACCESS POINT MODELS USING CLUSTERING TECHNIQUES

    公开(公告)号:US20200154392A1

    公开(公告)日:2020-05-14

    申请号:US16068568

    申请日:2017-06-21

    Applicant: Google LLC

    Abstract: The technology relates to generating a wireless network access point model for determining locations within an area. In one example, a plurality of scan vectors, each scan vector representing a set of signal strengths for a set of wireless network access point identifiers and being associated with a location within the area at which a mobile device moving through the area measured the set of signal strengths are received. A set of clusters is generated by iterating through a split phase until the number of clusters in the set of clusters equals a maximum number of clusters or there are no bad scan vectors identified. A bad scan vector may include a vector having a vector difference from a center of a cluster to which that vector is assigned is less than a minimum similarity value. The set of cluster is then used to generate the model of the area.

    Systems and Methods of Determining an Improved User Location Using Real World Map and Sensor Data

    公开(公告)号:US20240272308A1

    公开(公告)日:2024-08-15

    申请号:US18642564

    申请日:2024-04-22

    Applicant: Google LLC

    CPC classification number: G01S19/50 G01C21/206 G01S5/0269

    Abstract: A method for revising an initial estimate of a location of a user device includes obtaining an initial estimate of a location of a user device; obtaining maps information corresponding to a first geographic area associated with the initial estimate, the first geographic area including one or more features; obtaining sensor data from one or more sensors; determining a mode of travel based on the sensor data; determining a set of permissible areas that can potentially include the user device, based on the one or more features of the first geographic area and the mode of travel; and revising the initial estimate to provide a revised estimate for the location of the user device when the set of permissible areas encompass a second geographic area which is different than the first geographic area associated with the initial estimate of the location of the user device.

    Generating wireless network access point models using clustering techniques

    公开(公告)号:US10820296B2

    公开(公告)日:2020-10-27

    申请号:US16068568

    申请日:2017-06-21

    Applicant: Google LLC

    Abstract: The technology relates to generating a wireless network access point model for determining locations within an area. In one example, a plurality of scan vectors, each scan vector representing a set of signal strengths for a set of wireless network access point identifiers and being associated with a location within the area at which a mobile device moving through the area measured the set of signal strengths are received. A set of clusters is generated by iterating through a split phase until the number of clusters in the set of clusters equals a maximum number of clusters or there are no bad scan vectors identified. A bad scan vector may include a vector having a vector difference from a center of a cluster to which that vector is assigned is less than a minimum similarity value. The set of cluster is then used to generate the model of the area.

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