Quantification of GNSS NLOS Spatial Correlation: A Case Study in Hong Kong's Urban Canyon

Research output: Chapter in book/report/conference proceedingConference contributionResearchpeer review

Authors

  • Lucy Icking
  • Guohao Zhang
  • Li Ta Hsu
  • Steffen Schön

Research Organisations

External Research Organisations

  • Hong Kong Polytechnic University
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Details

Original languageEnglish
Title of host publicationProceedings of the 2022 International Technical Meeting of The Institute of Navigation, ITM 2022
Pages712-722
Number of pages11
ISBN (Electronic)9780936406305
Publication statusPublished - 2022
Event2022 International Technical Meeting of The Institute of Navigation, ITM 2022 - Long Beach, United States
Duration: 25 Jan 202227 Jan 2022

Publication series

NameProceedings of the International Technical Meeting of The Institute of Navigation, ITM
Volume2022-January
ISSN (Print)2330-3662
ISSN (Electronic)2330-3646

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.

ASJC Scopus subject areas

Cite this

Quantification of GNSS NLOS Spatial Correlation: A Case Study in Hong Kong's Urban Canyon. / Icking, Lucy; Zhang, Guohao; Hsu, Li Ta et al.
Proceedings of the 2022 International Technical Meeting of The Institute of Navigation, ITM 2022. 2022. p. 712-722 (Proceedings of the International Technical Meeting of The Institute of Navigation, ITM; Vol. 2022-January).

Research output: Chapter in book/report/conference proceedingConference contributionResearchpeer review

Icking, L, Zhang, G, Hsu, LT & Schön, S 2022, Quantification of GNSS NLOS Spatial Correlation: A Case Study in Hong Kong's Urban Canyon. in Proceedings of the 2022 International Technical Meeting of The Institute of Navigation, ITM 2022. Proceedings of the International Technical Meeting of The Institute of Navigation, ITM, vol. 2022-January, pp. 712-722, 2022 International Technical Meeting of The Institute of Navigation, ITM 2022, Long Beach, United States, 25 Jan 2022. https://doi.org/10.33012/2022.18165
Icking, L., Zhang, G., Hsu, L. T., & Schön, S. (2022). Quantification of GNSS NLOS Spatial Correlation: A Case Study in Hong Kong's Urban Canyon. In Proceedings of the 2022 International Technical Meeting of The Institute of Navigation, ITM 2022 (pp. 712-722). (Proceedings of the International Technical Meeting of The Institute of Navigation, ITM; Vol. 2022-January). https://doi.org/10.33012/2022.18165
Icking L, Zhang G, Hsu LT, Schön S. Quantification of GNSS NLOS Spatial Correlation: A Case Study in Hong Kong's Urban Canyon. In Proceedings of the 2022 International Technical Meeting of The Institute of Navigation, ITM 2022. 2022. p. 712-722. (Proceedings of the International Technical Meeting of The Institute of Navigation, ITM). doi: 10.33012/2022.18165
Icking, Lucy ; Zhang, Guohao ; Hsu, Li Ta et al. / Quantification of GNSS NLOS Spatial Correlation : A Case Study in Hong Kong's Urban Canyon. Proceedings of the 2022 International Technical Meeting of The Institute of Navigation, ITM 2022. 2022. pp. 712-722 (Proceedings of the International Technical Meeting of The Institute of Navigation, ITM).
Download
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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.",
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