Quantifying GNSS Multipath Statistics by Signal Properties in Urban, Suburban, and Rural Environments
Abstract
Positioning solutions based on global navigation satellite systems remain vulnerable to local multipath and non-line-of-sight conditions, a challenge for autonomous systems that must operate reliably across diverse environments. To support context-aware navigation, we quantify pseudorange multipath effects across four environmental settings: canyon, urban, trees, and open sky. Given a known receiver position, the range-free double difference (RFDD) can be used to isolate multipath errors. We propose a refinement accounting for clock biases in a commercial off-the-shelf receiver, which otherwise distort geometric range estimates-a key input to the RFDD. Applying our method to data collected in Toulouse, France, we statistically analyze how multipath errors can be modeled as a function of carrier-to-noise ratio (C/N 0 ) within each labeled environmental context. Histograms and the first four moments-mean, variance, skewness, and kurtosis-offer complementary perspectives, showing that the multipath component of the RFDD may be described by a chi-square-like distribution.
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BibTeX
@article{arnim2026quantifying,
title = {{Quantifying GNSS Multipath Statistics by Signal Properties in Urban, Suburban, and Rural Environments}},
author = {Maximilian von Arnim and Damien Vivet, and Yoko Watanabe},
journal = {Navigation},
year = {2026},
month = aug,
doi = {10.33012/navi.790},
url = {https://hal.science/hal-05781276v1},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Quantifying GNSS Multipath Statistics by Signal Properties in Urban, Suburban, and Rural Environments
AU - Maximilian von Arnim
AU - Damien Vivet,
AU - Yoko Watanabe
PY - 2026
DA - 2026/08/31
JO - Navigation
DO - 10.33012/navi.790
UR - https://hal.science/hal-05781276v1
AB - Positioning solutions based on global navigation satellite systems remain vulnerable to local multipath and non-line-of-sight conditions, a challenge for autonomous systems that must operate reliably across diverse environments. To support context-aware navigation, we quantify pseudorange multipath effects across four environmental settings: canyon, urban, trees, and open sky. Given a known receiver position, the range-free double difference (RFDD) can be used to isolate multipath errors. We propose a refinement accounting for clock biases in a commercial off-the-shelf receiver, which otherwise distort geometric range estimates-a key input to the RFDD. Applying our method to data collected in Toulouse, France, we statistically analyze how multipath errors can be modeled as a function of carrier-to-noise ratio (C/N 0 ) within each labeled environmental context. Histograms and the first four moments-mean, variance, skewness, and kurtosis-offer complementary perspectives, showing that the multipath component of the RFDD may be described by a chi-square-like distribution.
SN - 0028-1522
ER -