Estimation of slant total electron content using new generation gps signals

Ionosphere is atmosphere's ionized plasma layer constructed of free ions resulted by the ionization of neutral molecules with the effects of high energy photons radiated from the sun. Ionosphere is a dispersive, nonhomogeneous, time and space dependent complex medium. It is affected by many other phenomenon like the earth's magnetic field and gravity. High frequency (HF) radio waves reflect from ionosphere and satellite signals are refracted at the ionosphere. Therefore, the realization of instant effects of ionosphere on signals is at critical importance for many systems. The ionospheric effects on signals are caused by the free charged particles in the ionosphere. The total free charged ions between two points in ionospheres is called the Total Electron Content (TEC). This parameter is used for defining ionospheric effects on signals with different frequencies. In this thesis study, the total electron content between one Global Positioning System (GPS) receiver and one GPS satellite called Slant Total Electron Content (STEC) is estimated. GPS signals are used in many different studies. In those studies the GPS signals with L1 and L2 frequencies are used to estimate STEC between one receiver station and one GPS satellite. In this thesis a new STEC estimation algorithm is proposed which includes new GPS signals with L5 frequency. Using this method separately pseudo range and phase data of different receiver and satellites are composed in equation sets and instantaneous low noise STEC estimations, instantaneous satellite bias estimations and receiver differential coded bias estimations are possible. This method is tested for different receiver stations located on different latitude regions of earth for quiet, positively disturbed and negatively disturbed days of ionosphere. The STEC results are compared with the STEC estimation of IONOLAB-STEC algorithm. The comparisons show results of the developed method is coherent with the TEC profile. The differences with two methods are caused by the usage of different bases. This new method developed in this thesis study proposes a new point of view in the STEC estimation processes by including the GPS signals with L5 frequency. In addition to STEC estimations, the satellite biases in L5 frequency and receiver differential code biases between L1-L2, L1-L5 and L2-L5 frequencies are estimated.