Preliminary assessment of the effect of noise on velocity uncertainty on the Nigerian permanent GNSS network

Abstract

With the evolution of GNSS technology, geodynamic activities can appropriately be modelled nowadays. GNSS derived time series from which velocities and their uncertainties are derived, are vital derivatives in geodynamic modelling processes. Therefore, understanding all the stochastic properties is crucial. Assuming that GNSS coordinate time series is characterized by only white noise may lead to underestimation of velocity uncertainties. In this contribution, noise behaviour of NigNET tracking stations position time series was examined by adopting WN, FL+WN, WN+RW, WN+PL. Using the maximum likelihood estimate (MLE), Akaike Information Criteria (AIC) and Bayesian Information Criteria (BIC) the quality of stochastic model or the goodness of fit of a stochastic model is determined. The results of this study show that the combination of white plus flicker noise is the best model for describing the stochastic part of NigNET tracking stations position time series.