The ionosphere is a layer of ionised gas in the upper layers of the atmosphere around the Earth that plays a critical role in satellite communication, military communication and space science. The influence that the ionosphere has on communication systems can be quantified if the distribution of the electron density within the ionosphere is known. Several methods and instruments to determine the distribution of electron density are currently being used: satellites, ionosondes, incoherent scatter radars and computerised ionospheric tomography based on dual-frequency GPS signals. The present study investigates a novel way of using GPS receivers on mobile platforms to achieve near real-time ionospheric characterisation over locations beyond the reach of land-based ionospheric characterisation methods. GPS observations were collected, pre-processed and inverted by means of tomography to generate three-dimensional electron density maps. These electron density maps were analysed and verified. The viability of using observations from a mobile GPS receiver for ionospheric tomography was investigated. The algorithms were verified by means of a model ionosphere and a simulated GPS receiver. Furthermore, electron density maps generated from GPS observables from a mobile receiver were verified against ionosonde-derived electron density profiles, static land-based GPS receivers and known high-frequency propagation paths using propagation path prediction. The results were evaluated and the conclusion was that, although some aspects still have to be addressed, a dual-frequency GPS receiver on a ship can provide useful ionospheric characterisation in areas which are otherwise poorly or not covered by land-based receivers. / Dissertation (MEng)--University of Pretoria, 2011. / Electrical, Electronic and Computer Engineering / unrestricted

Detailed study of the spatial correlations of day-to-day ionospheric TEC variations on a global scale was performed for four 30-day-long periods in 2004 (January, March/April, June/July, September/October) using observations from more than 1000 ground-based GPS receivers. In order to obtain the spatial correlations, initially, the day-to-day variability was calculated by first mapping the observed slant TEC values for each 5-minute GPS ground receiver-satellite pair to the vertical and then differencing it with its corresponding value from the previous day. This resulted in more than 150 million values of day-to-day change in TEC (delta TEC). Next, statistics were performed on the delta TEC values. The study indicates strong correlationsbetween geomagnetic conjugate points, and these correlations are larger at low latitudes than at middle latitudes. Typical correlation lengths, defined as the angular separation at which the correlation coefficient drops to 0.7, were found to be larger at middle latitudes than at low latitudes. The correlation lengths are larger during daytime than during nighttime. The results indicate that the spatial correlation is largely independent of season. These spatial correlations are important for understanding the physical mechanisms that cause ionospheric weather variability and are also relevant to data assimilation. In an effort to better understand the effects of neutral wind and electric field on the TEC variability, a physics-based numerical Ionosphere/Plasmasphere Model (IPM) was used. The model solves the transport equations for the six ions, O+, NO+, O2+, N2+, H+, and He+, on convecting flux tubes that realistically follow the geomagnetic field. Two of the inputs required by the IPM are the thermospheric neutral wind and the low-latitude electric field, which can be given by existing empirical model or externally specified by the user. To study the relative importance of the neutral wind and the electric field for the TEC variations, these two model inputs were externally modified and the resulting variations in TEC were compared. Neutral wind and electric field modifications were introduced at three different local times in order to investigate the effect of different start times of the imposed perturbations on TEC. This study focused on modeled low- and middlelatitude TEC variations in the afternoon and post-sunset at three different longitude sectors for medium solar activity and low geomagnetic activity. The largest changes in TEC were found predominantly in the equatorial anomaly, and a significant longitudinal dependence was observed. The results indicate that the perturbation effect on the TEC at 2100 LT varied nonlinearly with the elapsed time after the imposed neutral wind and electric field perturbations. An important outcome of this study is that daytime neutral wind and/or electric field modifications will lead to essentially identical TEC changes in the 2100 local time sector.

電離層延遲為精密GPS定位及導航的主要誤差來源之一，為了減弱電離層延遲對GPS定位及導航的影響，可以利用雙頻GPS觀測量構建即時的區域電離層模型，以提供即時的電離層延遲誤差改正參數，修正因電離層延遲效應造成的定位及導航誤差。 本研究以台灣地區雙頻GPS觀測量，採用相位水準技術估算全電子含量（TEC）、修正的單站演算法估計各GPS衛星及接收儀之L1/L2差分延遲及以UNSW網格式演算法構建區域的電離層模型。並進而求得適合台灣南部地區網格式電離層模型之較佳網格大小及探討使用那些內政部衛星追蹤站的觀測資料，便可有效建立台灣地區的電離層模型。 / The ionospheric delay is one of the main sources of error in precise GPS positioning and navigation. The magnitude of the ionospheric delay is related to the Total Electron Content (TEC) along the radio wave path from a GPS satellite to the ground receiver. The TEC is a function of many variables, including long and short term changes in solar ionising flux, magnetic activity, season of the year, time of day, user location and viewing direction. A dual-frequency GPS receiver can eliminate (to the first order) the ionospheric delay through a linear combination of L1 and L2 observables. However, the majority of civilians use low-cost single-frequency GPS receivers that cannot use this option. Consequently, it is beneficial to estimate ionospheric delays over the region of interest, in real-time, in support of single-frequency GPS positioning and navigation applications. In order to improve real-time regional ionosphere modelling performance, a grid-based algorithm is proposed. Data from the southern Taiwan region GPS network were used to test the ionosphere modelling algorithms. From the test results described here, it is shown that the performance of real-time regional ionosphere modelling is improved significantly when the proposed algorithm is used.