Perpustakaan Digital ITB

Vertical Total Electron Content (VTEC) is a critical parameter of the ionosphere that significantly affects the propagation of radio signals. Accurate estimation of VTEC is essential for many applications, such as positioning, satellite communication, and space weather forecasting. The spatial and temporal resolution of Global Ionospheric Maps (GIMs) from the International GNSS Service (IGS), Center for Orbit Determination in Europe (CODE), and International Reference Ionosphere (IRI-2020) models are limited in regions with a sparse or limited network of receivers, particularly in Nigeria. Satellite and receiver Differential Code Biases (DCBs) are one of the major sources of error in Global Navigation Satellite Systems (GNSS) positioning that must be considered for accurate estimation of VTEC. However, the DCBs of receivers not belonging to the IGS network are unavailable from the GIM. To overcome these challenges, we attempt to develop and compare the performance of two innovative VTEC estimation methods based on single and networks of receivers utilizing spherical harmonic expansion and orthogonal transformation techniques. Our novel methods leverage multi-GNSS observations to accurately estimate VTEC, satellite, and receiver DCB. GNSS RINEX, IONEX, and SP3 data from 2011 across 9 multi-GNSS receivers in the Nigerian Geodetic Network sampled at 30-second intervals were utilized for this study. Code pseudo-range observations were also smoothed with carrier phase observations and utilized for this study. To ensure the validity of results and data quality, we performed various preprocessing steps using both the Melbourne-Wubbena linear and the geometry-free linear combinations using an in-house ITB-GNSSTEC program based on batch processing and the least squares techniques. The single station-based method leverages a single GNSS receiver to estimate VTEC at a temporal resolution of 1 hour. The single-receiver method exhibits notable agreement upon comparison with estimates from the IGS, CODE, and IRI-2020 models during both quiet and disturbed periods of geomagnetic activity, presenting a standard deviation range of 2.882 to 7.362 TECU and correlation coefficients ranging from 0.898 to 0.980 at various independent stations. The network-based method utilized data from a network of nine GNSS receivers in the Nigerian Geodetic Network (NIGNET), achieving an unprecedented 10-minute temporal resolution, and enhancing VTEC estimation capabilities over Nigeria. Comparisons with the established models also show strong correlations during various conditions, exhibiting standard deviations within 2.8 to 6.5 TECU and correlation coefficients exceeding 0.92. Spectral analysis of VTEC estimates from the network-based model identifies prominent diurnal, semi-diurnal, and sub-diurnal frequency components. Seasonal analysis highlights the highest mean VTEC in September Equinox and December Solstice, and the lowest during June Solstice. In comparing the two methods, the single-receiver method provides a lower temporal resolution of 1 hour, while the network-based model offers a higher resolution of 10 minutes. The daily VTEC patterns from both methods reveal the lowest values in the early morning, a midday peak, occasional double peaks, and post-sunset enhancements, especially during equinoxes. Both models perform well during periods of geomagnetic activity and were able to capture post-sunset VTEC enhancements. Additionally, both methods successfully estimated Differential Code Biases (DCBs) for GPS and GLONASS, aligning closely with CODE estimates. Our results suggest that the network-based model is more suited for capturing rapid changes, while the single-receiver model is advised for applications requiring moderate temporal resolution and may be a good choice for VTEC modeling, particularly in areas with sparse network coverage. This research has contributed to developing high-resolution VTEC methods for estimating VTEC, satellite, and receiver DCBsfor areas with sparse distribution of GNSS receivers. Hence, enabling the detection of local ionospheric characteristics missed by GIM models. This research significantly advances the understanding of VTEC modeling and its characteristics in Nigeria, offering a valuable tool for precise positioning, satellite communication, and space weather forecasting.