A Segmented Weighting and Elimination Method for GNSS Diffraction Errors in Urban Building Obstruction Environments

Le résumé fourni par la source

In densely built urban environments, GNSS signals frequently undergo diffraction at building edges, and the resulting errors can severely degrade positioning accuracy and reliability. Previous studies have shown a strong correlation between diffraction error and the carrier-power-to-noise-density ratio (C/N0). Building on this observation, this study proposes a GNSS diffraction-mitigation method based on segmented down-weighting and exclusion of affected observations. First, an open-sky reference model of the elevation–C/N0 relationship is established for each satellite class. A robust strategy is then introduced to adaptively down-weight moderately contaminated observations and remove severely affected ones during stochastic modeling. The proposed method is evaluated using both static and kinematic datasets collected in dense urban environments. In the static experiment under severe building obstruction, the ambiguity-fixing rate (AFR) reaches 95.5%, with horizontal and vertical accuracies of 4 mm and 8 mm, respectively, substantially outperforming conventional weighting strategies. In the vehicle-based kinematic experiment, the fixed-solution rate exceeds 80%, and the float solution is also noticeably improved relative to traditional weighting and exclusion methods. Overall, the proposed method effectively mitigates diffraction-induced errors and improves positioning performance in dense urban environments, with potential applications in automated inspection, intelligent construction, and high-precision deformation monitoring.

Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.