Quantification of GNSS NLOS Spatial Correlation

A Case Study in Hong Kong's Urban Canyon

authored by: Lucy Icking, Guohao Zhang, Li Ta Hsu, Steffen Schön
Abstract: In urban environments, non-line-of-sight (NLOS) signal conditions are a major error contributor for GNSS positioning, the signal delay can reach up to more than one hundred meters due to reflection in urban canyons such as Hong Kong. Collaborative positioning between traffic participants can help to eliminate common errors, but comprehensive analyses on how to find common errors in cities and how to quantify them are required. In this study, we present a new method for finding locations in urban areas with similar extra path delays on the basis of ray-tracing with 3D building models, exemplarily for an urban canyon in Hong Kong. Using the 2D Pearson correlation coefficient, we calculate the spatial correlation of reflection extra paths at two locations to generate a similarity measure. With this measure, we quantify the amount of similar errors at two locations. In realistic simulations, we show that two locations with highly correlated extra path delays show better results concerning single-difference error correction and relative positioning errors. The single differences show that for the selected area in Hong Kong, the higher the spatial correlation, the higher the amount of common extra path delays. Furthermore, we are able to show that the mean relative positioning error can be reduced from 42.4 m for a low correlation pair of agents to 12.7 m for a high spatial correlation pair.
Organisation(s): Institute of Geodesy
External Organisation(s): Hong Kong Polytechnic University
Type: Conference contribution
Pages: 712-722
No. of pages: 11
Publication date: 2022
Publication status: Published
Peer reviewed: Yes
ASJC Scopus subject areas: Aerospace Engineering, Electrical and Electronic Engineering
Electronic version(s): https://doi.org/10.33012/2022.18165 (Access: Closed)
: Details in the research portal "Research@Leibniz University"

BibTeX

@inproceedings{cfc2cb860ed34817a74742f970dcd84d,
title = "Quantification of GNSS NLOS Spatial Correlation: A Case Study in Hong Kong's Urban Canyon",
abstract = "In urban environments, non-line-of-sight (NLOS) signal conditions are a major error contributor for GNSS positioning, the signal delay can reach up to more than one hundred meters due to reflection in urban canyons such as Hong Kong. Collaborative positioning between traffic participants can help to eliminate common errors, but comprehensive analyses on how to find common errors in cities and how to quantify them are required. In this study, we present a new method for finding locations in urban areas with similar extra path delays on the basis of ray-tracing with 3D building models, exemplarily for an urban canyon in Hong Kong. Using the 2D Pearson correlation coefficient, we calculate the spatial correlation of reflection extra paths at two locations to generate a similarity measure. With this measure, we quantify the amount of similar errors at two locations. In realistic simulations, we show that two locations with highly correlated extra path delays show better results concerning single-difference error correction and relative positioning errors. The single differences show that for the selected area in Hong Kong, the higher the spatial correlation, the higher the amount of common extra path delays. Furthermore, we are able to show that the mean relative positioning error can be reduced from 42.4 m for a low correlation pair of agents to 12.7 m for a high spatial correlation pair.",
author = "Lucy Icking and Guohao Zhang and Hsu, {Li Ta} and Steffen Sch{\"o}n",
note = "Funding Information: This work was supported by the German Research Foundation (DFG) as part of the Research Training Group Integrity and Collaboration in Dynamic Sensor Networks (i.c.sens) [RTG 2159], as well as the Germany/Hong Kong Joint Research Scheme funded by the Research Grant Council (RGC) in Hong Kong and the German Academic Exchange Service (DAAD).; 2022 International Technical Meeting of The Institute of Navigation, ITM 2022 ; Conference date: 25-01-2022 Through 27-01-2022",
year = "2022",
doi = "10.33012/2022.18165",
language = "English",
series = "Proceedings of the International Technical Meeting of The Institute of Navigation, ITM",
publisher = "Institute of Navigation",
pages = "712--722",
booktitle = "Proceedings of the 2022 International Technical Meeting of The Institute of Navigation, ITM 2022",
}