MULTIPATH ERROR

This study presents the stochastic modeling and quantification of multipath error in static Global Navigation Satellite System (GNSS) observations processed using RTKLIB. Multipath remains a major source of positioning inaccuracy, particularly in obstructed environments. The research statistically characterizes multipath and evaluates its contribution to overall observation uncertainty through a data-driven modeling approach. Static GNSS data were collected under two contrasting conditions, an open-sky environment and a multipath-prone site, using Tersus GNSS receivers. Pseudorange residuals, satellite elevation angles, and carrier-to-noise ratios (C/N₀) were extracted from RTKLIB output files and filtered with a Python-based parser to ensure consistency. The cleaned datasets were then used to develop a stochastic model expressing observation variance as a function of satellite elevation and signal strength. Parameter estimation employed least squares and non-negative least squares (NNLS) regression to ensure physically meaningful variance predictions. Results from the open-sky dataset revealed a baseline variance (σ₀²) of 0.000000 m² and an elevation-dependent coefficient a₁ = 1.6456, indicating stable, low-noise observations. The multipath-prone site exhibited a much larger baseline variance (σ₀² = 142.97 m²) and stronger elevation and signal dependency (a₁ = 10.063, a₂ = 4.79 × 10⁸), reflecting severe distortion from signal reflection. About 25% of pseudorange variance in open-sky conditions was explained by elevation and C/N₀, slightly less under multipath due to irregular reflections. Multipath variances showed heavy-tailed distributions, with 95th-percentile values of 2,726 m² (≈52.2 m) under multipath and 63.6 m² (≈8.0 m) in open-sky conditions. Certain PRNs were consistently more affected, confirming the directional dependency of multipath. The developed stochastic model effectively relates satellite geometry and signal strength to pseudorange
precision, providing a reliable framework for improving GNSS accuracy in multipath environments