Including drone attitude in SKA calibration

The Square Kilometer Array will be one of the main astronomical instruments of the 21 century. The Array will be composed of two types of telescopes, the SKA-Mid and SKA-Low. The SKA-Low will consist of multiple stations, each station will be composed of 256 SKALA (Square Kilometer Log-periodic Antenna) antennas. In order to acquire high resolution images, a calibration of the arrays will need to be achieved. The Far-Field calibration of such array will require artificial signal sources such as antennas mounted on Unmanned Aerial Vehicle (UAV). Previous investigation has proven that Far-Field calibration error was mainly due to the UAV attitude errors. This thesis focuses on the reduction of the calibration error by calculating the UAV attitudes using the SKALA elements composing the SKA stations. The HARP software is used in order to calculate the embedded element pattern (EEP) of each antenna. The calculation of the voltage received by the illumination of the array using the UAV is detailed and verified. We develop a method to calculate the UAV attitudes allowing to improve the calculation of the calibration coefficients of the array. The Levenberg-Marquardt and Nelder-Mead algorithms are used and a performance comparison is carried out for each algorithm. The impact of the thermal noise of the low noise amplifier (LNA) and the sky is modelled in the received voltage. The impact of this thermal noise on the accuracy of the calibration calculation, using the developed algorithm, focused on.