MODELLING THE EFFECT OF LOCAL TROPOSPHERIC DELAY IN GLOBAL NAVIGATION SATELLITE SYSTEM OBSERVATIONS FOR ENHANCED GEODETIC POSITIONING

Abstract

Tropospheric delay is a major source of error in Global Navigation Satellite Systems (GNSS) applications. All satellite signals propagated from satellite to ground receiver are influenced by effects of atmospheric refraction, referred to as tropospheric delays. The effects of tropospheric delays in the GNSS signals affect accuracies of position estimates derived from the GNSS. The objectives of this research are to assess the trends and evolution in techniques for estimating the effect of tropospheric errors in GNSS positioning; evaluate the accuracies of existing techniques applied in estimating tropospheric delays in a local GNSS Network; develop a local model for estimating the spatial and temporal variations of tropospheric delays in a local GNSS Network; and evaluate the accuracy of geodetic positioning in applying newly developed local tropospheric delay model estimates over the existing global estimates. Several existing models have been developed and applied in estimating parameters required for mitigating the tropospheric effect. However, evaluations of these models within the local GNSS networks have shown degraded accuracies over the study area, attributed to the fact that data used in developing these existing models were based on broad global estimated parameters with poor data assimilation within the region of study. This necessitated the development of a model for local tropospheric delay estimation, for an improved positioning accuracy within the study area. The study area adopted in this research focuses on the Nigerian GNSS Network. Tropospheric delay parameter modelled is the Zenith Tropospheric Delays (ZTD). Data used for the modelling are ZTD derived from direct GNSS observation and supplemented by improved ray-traced Numerical Weather Model (NWM) ZTD. GNSS observations were post-processed using the Precise Point Positioning (PPP) strategy. This was implemented using the GNSS Analysis and Processing Software (GAPS), which simultaneously estimates point position coordinate and tropospheric delay parameters using iterative least square approach. Model development was carried out by method of training an Artificial Neural Network (ANN) to derive optimal network parameters. For the purpose of model evaluation, numerical investigation was carried out by processing using new local model and existing global ZTD estimates. Model validations were also performed using hypothesis testing, internal and external data validations. Results from model validations in all cases indicated evidences of improvements over existing global models. A model for estimating the effect of local tropospheric delay that have led to an improved geodetic positioning accuracy, has been developed. Consequently, the newly developed local tropospheric delay model is recommended for GNSS applications requiring geodetic accuracies in and around the study area.