| Grant number: | 12/19906-7 |
| Support Opportunities: | Regular Research Grants |
| Start date: | March 01, 2013 |
| End date: | February 28, 2015 |
| Field of knowledge: | Physical Sciences and Mathematics - Geosciences - Geodesy |
| Principal Investigator: | Daniele Barroca Marra Alves |
| Grantee: | Daniele Barroca Marra Alves |
| Host Institution: | Faculdade de Ciências e Tecnologia (FCT). Universidade Estadual Paulista (UNESP). Campus de Presidente Prudente. Presidente Prudente , SP, Brazil |
| Associated researchers: | Eniuce Menezes de Souza ; Haroldo Antonio Marques ; Luiz Fernando Sapucci ; Milton Hirokazu Shimabukuro ; Tayná Aparecida Ferreira Gouveia |
Abstract
In the past few years is increasing the necessity of realizing high accuracy positioning. In this sense, the spatial technologies have being widely used. The GNSS (Global Navigation Satellite System) has revolutionized the geodetic positioning activities. Among the existent methods one can emphasize the network-based positioning. Applying this method is possible to obtain centimetric accuracy in real time. But, in order to get the intended accuracy, mainly in real time, is indispensable to realize the atmospheric modeling (ionosphere and troposphere) accordingly. Related to troposphere, there are the empirical models (for example Saastamoinem and Hopfield). But when highly accuracy results (error of few centimeters) are desired, maybe these models are not appropriated to the Brazilian reality. In order to minimize this limitation arise the NWP (Numerical Weather Prediction) models. Other extremely important factors concerning the positioning are the errors due to ionosphere. The ionospheric refraction is one of the most important error sources in GNSS positioning. A great part of Brazilian territory is located in geomagnetic equator, that is severely affected by ionosphere. In this research the main goal is to accomplish a rigorous analysis concerning the use of troposphere NWP models and ionosphere grid and/or regional models in network-based positioning. The expected result of this research is to make available a product that uses such models in order to generate virtual reference station data with great quality employing the network-based positioning. (AU)
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