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Numerical Simulations to Assess ART and MART Performance for Ionospheric Tomography of Chapman Profiles Anais da ABC (AABC)
PROL,FABRICIO S.; CAMARGO,PAULO O.; MUELLA,MARCIO T.A.H..
ABSTRACT The incomplete geometrical coverage of the Global Navigation Satellite System (GNSS) makes the ionospheric tomographic system an ill-conditioned problem for ionospheric imaging. In order to detect the principal limitations of the ill-conditioned tomographic solutions, numerical simulations of the ionosphere are under constant investigation. In this paper, we show an investigation of the accuracy of Algebraic Reconstruction Technique (ART) and Multiplicative ART (MART) for performing tomographic reconstruction of Chapman profiles using a simulated optimum scenario of GNSS signals tracked by ground-based receivers. Chapman functions were used to represent the ionospheric morphology and a set of analyses was conducted to assess ART and MART...
Tipo: Info:eu-repo/semantics/article Palavras-chave: Grid-based tomography; Electron density; Ionospheric profile; Chapman function; GNSS; TEC.
Ano: 2017 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652017000401531
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Hybrid Geoid Model: Theory and Application in Brazil Anais da ABC (AABC)
ARANA,DANIEL; CAMARGO,PAULO O.; GUIMARÃES,GABRIEL N..
Determination of the ellipsoidal height by Global Navigation Satellite Systems (GNSS) is becoming better known and used for purposes of leveling with the aid of geoid models. However, the disadvantage of this method is the quality of the geoid models, which degrade heights and limit the application of the method. In order to provide better quality in transforming height using GNSS leveling, this research aims to develop a hybridization methodology of gravimetric geoid models EGM08, MAPGEO2015 and GEOIDSP2014 for the State of São Paulo, providing more consistent models with GNSS technology. Radial Basis Function (RBF) neural networks were used to obtain the corrector surface, based on differences between geoid model undulations and the undulations obtained...
Tipo: Info:eu-repo/semantics/article Palavras-chave: EGM08; GEOIDSP2014; GNSS leveling; MAPGEO2015; Neural network.
Ano: 2017 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652017000401943
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