O impacto de vários fatores na qualidade de parâmetrtos neutrosféricos de estação a partir do processamento de dados gnss

Abstract

Propagation delays of the signals of global navigation satellite systems (GNSS) caused by the neutral atmosphere are an important accuracy-limiting factor for precise geodetic applications. A common approach to handle the neutrospheric delay is to estimate so-called site-specific neutrospheric parameters (SSNP) within GNSS data processing which are then combined with the predicted model values calculated primarily based on meteorological data. Therefore, the quality of the determined neutrospheric delay depends not only on the factors impacting the GNSS signals but also on data processing strategies. In this paper, the influence of the factors impacting neutrospheric modelling such as baseline length, multipath, observation weighting, ambiguity resolution, and neutrospheric prediction models are analysed and quantified based on the standard deviations of the estimated SSNP. Additionally, an improved observation weighting scheme based on signal-to-noise power ratio measurements is briefly described. Test results indicate that applying this advanced weight model within GNSS data processing, including observations at low elevation, the standard deviation of the estimated SSNP can be improved by nearly 25% compared with the standard elevation-dependent weighting model.