Paper Info
Title
Feasibility Study of Using Mobile Laser Scanning Point Cloud Data for GNSS Line of Sight Analysis.
Abstract
Thepositioning accuracywith good GNSS observation can easily reach centimetre level, supported by advanced GNSS technologies. However, it is still a challenge to offer a robust GNSS based positioning solution in a GNSS degraded area. The concept of GNSS shadowmatching has been proposed to enhance the GNSS based position accuracy in city canyons, where the nearby high buildings block parts of the GNSS radio frequency (RF) signals. However, the results rely on the accuracy of the utilized ready-made 3D city model. In this paper, we investigate a solution to generate a GNSS shadow mask with mobile laser scanning (MLS) cloud data. The solution includes removal of noise points, determining the object which only attenuated the RF signal and extraction of the highest obstruction point, and eventually angle calculation for the GNSS shadow mask generation. By analysing the data with the proposed methodology, it is concluded that the MLS point cloud data can be used to extract the GNSS shadow mask after several steps of processing to filter out the hanging objects and the plantings without generating the accurate 3D model, which depicts the boundary of GNSS signal coverage more precisely in city canyon environments compared to traditional 3D models.
Year
DOI
Venue
2017
10.1155/2017/5407605
MOBILE INFORMATION SYSTEMS
Field
DocType
Volume
Shadow,Shadow mask,Telecommunications,Computer science,Remote sensing,Air navigation,GNSS augmentation,Radio frequency,GNSS applications,Point cloud,Cloud computing,Distributed computing
Journal
2017
ISSN
Citations 
PageRank 
1574-017X
0
0.34
References 
Authors
10
8
Name
Order
Citations
PageRank
Yuwei Chen112923.23
lingli zhu21069.87
Jian Tang3132259.93
Ling Pei4899.43
Antero Kukko548347.44
Yiwu Wang600.68
Juha Hyyppä743966.75
Hannu Hyyppa820223.16