Title: Exclusion of GNSS NLOS Receptions Caused by Dynamic Objects in Heavy Traffic Urban Scenarios Using Real-Time 3D Point Cloud: An Approach without 3D Maps,
Abstract: Absolute positioning is an essential factor for the arrival of autonomous
driving. Global Navigation Satellites System (GNSS) receiver provides absolute
localization for it. GNSS solution can provide satisfactory positioning in open
or sub-urban areas, however, its performance suffered in super-urbanized area
due to the phenomenon which are well-known as multipath effects and NLOS
receptions. The effects dominate GNSS positioning performance in the area. The
recent proposed 3D map aided (3DMA) GNSS can mitigate most of the multipath
effects and NLOS receptions caused by buildings based on 3D city models.
However, the same phenomenon caused by moving objects in urban area is
currently not modelled in the 3D geographic information system (GIS). Moving
objects with tall height, such as the double-decker bus, can also cause NLOS
receptions because of the blockage of GNSS signals by surface of objects.
Therefore, we present a novel method to exclude the NLOS receptions caused by
double-decker bus in highly urbanized area, Hong Kong. To estimate the geometry
dimension and orientation relative to GPS receiver, a Euclidean cluster
algorithm and a classification method are used to detect the double-decker
buses and calculate their relative locations. To increase the accuracy and
reliability of the proposed NLOS exclusion method, an NLOS exclusion criterion
is proposed to exclude the blocked satellites considering the elevation, signal
noise ratio (SNR) and horizontal dilution of precision (HDOP). Finally, GNSS
positioning is estimated by weighted least square (WLS) method using the
remaining satellites after the NLOS exclusion. A static experiment was
performed near a double-decker bus stop in Hong Kong, which verified the
effectiveness of the proposed method.