Função de mapeamento brasileira da atmosfera neutra e sua aplicação no posicionamento GNSS na América do Sul

• Ano de defesa: 2019
• Autor(a) principal: Gouveia, Tayná Aparecida Ferreira [UNESP]
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Estadual Paulista (Unesp)
• Palavras-chave em Português: Mapping function; Ray tracing; Neutral atmosphere modeling; Regional NWP; GNSS PPP; Função de mapeamento; Traçado de raio; Modelagem da atmosfera neutra; PNT regional; PPP GNSS
• Link de acesso: http://hdl.handle.net/11449/186250

Global Navigation Satellite Systems (GNSS) technology has been widely used in positioning, from day-to-day applications (metric accuracy) to applications that require high accuracy (few cm or dm). For high accuracy, different techniques may be applied to minimize the effects that the signal suffers from its transmission on the satellite to its reception. GNSS signal when propagating in the neutral atmosphere (from surface up to 50km) is influenced by hydrostatic gases and water vapor. The variation of these atmospheric constituents causes a refraction in the signal that generates a delay. This delay may cause errors of at least 2.5 m (zenith) and greater than 25 m (slant). The determination of the delay in the slanted direction (satellitereceiver) according to the elevation angle is performed by the mapping functions. One of the techniques for calculating the delay is raytracing. This technique allows us to map the actual path that the signal has traveled and to model the interference of the neutral atmosphere on it. Different approaches can be used to obtain information describing the neutral atmosphere constituents - temperature, pressure and humidity. The possibilities include the use of radiosonde measurements, weather and climate models (NWP), GNSS measurements, as well as theoretical models. Regional NWP models from the Center Weather Forecasting and Climate Studies (CPTEC) of the National Institute for Space Research (INPE) are a good alternative to provide atmospheric measurements, which describe the highly variable climate, according to the season and region of Brazil. In this research, these measurements were obtained from the NWP model of higher temporal (hourly) and spatial (5km) resolution, which started operations in 2018 as a regional model by CPTEC/INPE, named Weather Research and Forecasting (WRF). Considering the atmospheric variables obtained from the WRF, by applying the raytracing technique, the neutral atmosphere mapping function for Brazil and South America was developed, named Brazilian Mapping Function (BMF). BMF was used to obtain the knowledge and develop this methodology, which so far had not been carried out in Brazil. This function was evaluated in two approaches: regarding the quality of the delay; and precise point positioning (PPP) quality using BMF. In the first assessment of the zenith delay, we considered as reference the results from radiosonde and from data of four stations of the Brazilian Network for Continuous Monitoring of the GNSS Systems (RBMC), located in regions with distinct climatic characteristics (NAUS; CUIB; POLI; POAL). The period assessed was of one year of data, through which it was possible to verify the quality of the function in computing the zenith delay in the different seasons of the year. These results showed that the zenith delay obtained from BMF presented a maximum RMSE of 6 cm (in POAL) in relation to the reference data. Delay and inclined factor series were also generated, although they did not have reference data for statistical evaluation. They showed similar variability to the zenith delay (factor is the ratio between the inclined and zenith delays). In addition to these assessments, a preliminary analysis was performed to evaluate the contribution of BMF in PPP, with different strategies: one day of data processing; two stations; PPP static and kinematic mode; and different initialization times. In the quality assessment, the Vienna Mapping Function 1 (VMF1) was considered as a reference, whose results are from the global model of the European Center for Medium-Range Weather Forecasts (ECMWF). BMF also showed promising results for the post-processing positioning mode of high accuracy in the evaluated Brazilian regions. The best performance was obtained when it was applied to determine the a priori value of the PPP delay estimate, and closest to the NWP model analysis, the WRF at 12 UTC.