A GPS signal-in-space simulation model for equatorial and low latitudes in the Brazilian longitude sector

• Autor(a) principal: Surco Espejo, Teddy Modesto
• Data de Publicação: 2022
• Outros Autores: Costa, Emanoel, Moraes, Alison O., Martinon, André Ricardo Fazanaro, de Paula, Eurico Rodrigues, Monico, João Francisco Galera [UNESP]
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Institucional da UNESP
• Texto Completo: http://dx.doi.org/10.1007/s10291-022-01273-9; http://hdl.handle.net/11449/241673
• topic: Global positioning system; Ionospheric amplitude and phase scintillation; Ionospheric delay; Space weather

The ionosphere affects the propagation of global positioning system signals. Due to their special features, the equatorial and low-latitude ionosphere may produce particularly severe effects on them. The ground-based augmentation system has been developed to meet the safety requirements of civil aviation. To evaluate the performance of such a system, a statistical simulation model of the global positioning system signal-in-space has been developed, considering several components. The present work will focus on: (1) the ionospheric delay, with basis on statistical distributions of vertical total electron content obtained by the combination of the International Reference Ionosphere with data from the Rede Brasileira de Monitoramento Contínuo, operated by Instituto Brasileiro de Geografia e Estatística; (2) cycle ambiguity, characterized through the processing of the same data set; (3) ionospheric amplitude scintillation, simulated with basis on proper indices and the α–μ probability distribution; and (4) ionospheric phase scintillation, generated according to its standard deviation. The statistical simulation model is based on a set of representative geophysical parameters and may be used to generate time series of pseudorange, carrier phase, and received signal power, to be applied as inputs to existing or future ground-based augmentation system testbeds. This provides an alternative to experimental data collection, which could be expensive and time-consuming. Additionally, such data may not be available for all regions and critical geophysical conditions of interest.