Feasibility Study of Using Mobile Laser Scanning Point Cloud Data for GNSS Line of Sight Analysis

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Feasibility Study of Using Mobile Laser Scanning Point Cloud Data for GNSS Line of Sight Analysis. / Chen, Yuwei; Zhu, Lingli; Tang, Jian; Pei, Ling; Kukko, Antero; Wang, Yiwu; Hyyppä, Juha; Hyyppä, Hannu.

In: MOBILE INFORMATION SYSTEMS, Vol. 2017, 5407605, 2017.

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@article{8c5a593b1d2b483f972a992c6643dc7c,
title = "Feasibility Study of Using Mobile Laser Scanning Point Cloud Data for GNSS Line of Sight Analysis",
abstract = "The positioning accuracy with 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 shadow matching 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.",
author = "Yuwei Chen and Lingli Zhu and Jian Tang and Ling Pei and Antero Kukko and Yiwu Wang and Juha Hyypp{\"a} and Hannu Hyypp{\"a}",
year = "2017",
doi = "10.1155/2017/5407605",
language = "English",
volume = "2017",
journal = "MOBILE INFORMATION SYSTEMS",
issn = "1574-017X",

}

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TY - JOUR

T1 - Feasibility Study of Using Mobile Laser Scanning Point Cloud Data for GNSS Line of Sight Analysis

AU - Chen, Yuwei

AU - Zhu, Lingli

AU - Tang, Jian

AU - Pei, Ling

AU - Kukko, Antero

AU - Wang, Yiwu

AU - Hyyppä, Juha

AU - Hyyppä, Hannu

PY - 2017

Y1 - 2017

N2 - The positioning accuracy with 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 shadow matching 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.

AB - The positioning accuracy with 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 shadow matching 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.

UR - http://www.scopus.com/inward/record.url?scp=85015860742&partnerID=8YFLogxK

U2 - 10.1155/2017/5407605

DO - 10.1155/2017/5407605

M3 - Article

VL - 2017

JO - MOBILE INFORMATION SYSTEMS

JF - MOBILE INFORMATION SYSTEMS

SN - 1574-017X

M1 - 5407605

ER -

ID: 14578938