Analysis of the visibility of GPS satellites in the urban environment using point cloud representation

Master thesis (2024)

Authors

A.I. Gheorghiu Architecture and the Built Environment

Contributors

E. Verbree Digital Technologies - Architecture and the Built Environment (supervisor 1)
B.M. Meijers Digital Technologies - Architecture and the Built Environment (supervisor 2)
J.J.J.G. Hoogenboom Digital Technologies - Architecture and the Built Environment (supervisor 2)
Faculty
Architecture and the Built Environment
Copyright: © 2024 Irina Gheorghiu
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Published Date

19-01-2024

Language

English

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Faculty

Architecture and the Built Environment

Abstract

Global Navigation Satellite System is a spatial data acquisition technique, mostly used in navigation and positioning. One of the main components of this technique is the satellite visibility, which refers to the connection between the satellite and the ground receiver. It is known that the GNSS positioning systems are not as performing in urban areas due to the dense coverage of obstacles (buildings, trees, high terrain etc.). These obstacles can obstruct and reflect the lines of sight between the satellite and the ground receiver which can affect the quality of the performance of the GNSS service. The geometry configuration of the satellites above the receiver is another important aspect that has to be taken into consideration.

This research focuses on implementing a simulation similar to that of GNSS mission planning tools, but using point cloud data as the 3D representation of the surroundings of the receiver and using only the GPS constellation of satellites. Due to the large size of a point cloud sample, two visibility algorithms have been implemented to filter the necessary 3D data. The main output of the simulation are the dilution of precision values which give further information about the satellites' positions. The main purpose of this research is to understand the dilution of precision values, which are directly related to the geometry of the satellite configuration above the receiver. Understanding the behaviour and how the receiver's environment influences the DoP values can result in leading GNSS surveying missions with better results.

This output is then compared with the data acquired from a GNSS receiver in a real scenario. While the results are not favorable for the implemented simulation, it gives a better understanding of the surroundings of the receiver's location by using point cloud data than the already existing online GNSS tools.