GNSS POSITIONING USING THREE-DIMENSIONAL BUILDING MODELS

摘要

Techniques for GNSS positioning using three-dimensional (3D) building models are described. A processor of a mobile device can determine a lower bound of uncertainty for an estimated position of the mobile device. The processor can receive an estimated position from a GNSS receiver of the mobile device. The processor can acquire geographic feature data including 3D building models of buildings and other geographic features that are located near the estimated position and may reflect GNSS signals. The processor can then determine a lower bound of uncertainty of the estimated position, regardless of an estimated uncertainty provided by a GNSS estimator. The lower bound can be higher (e.g., have a greater error margin) than the uncertainty value provided by the GNSS estimator. The processor can then present the estimated position, in association with an error margin corresponding to the lower bound of uncertainty, on a map user interface of the mobile device.

主权项

1. A method comprising:
receiving, by a processor of a mobile device and from a global navigation satellite system (GNSS) receiver, an estimated position of the mobile device, the estimated position including estimated geographic coordinates and being associated with an uncertainty value; receiving geographic feature data, the geographic feature data including locations and heights of geographic features that are located sufficiently close to the estimated position to interfere with signals received by the GNSS receiver; determining, based on at least one of the locations of the geographic features, a count of the geographic features, or the heights of the geographic features, a lower bound of uncertainty of the estimated position that is achievable by the GNSS receiver when the GNSS receiver is located among the geographic features; and designating a representation of the lower bound of uncertainty as a new uncertainty value of the estimated position, including increasing the uncertainty value upon determining that the uncertainty value has smaller error margin than the lower bound of uncertainty.