In the ADome project, a truncated icosahedron is used as a frame for multiple antenna nodes. These nodes are used to measure the radiation pattern of an antenna-under-test located in the center of this dome. Since these antennas can be placed anywhere in the ADome by the user, a calibration system is necessary to find the spherical coordinates of each of these antennas. In this thesis, a method is proposed that uses computer vision algorithms, written using the OpenCV library in C++, to locate each of these antennas by detecting controllable LEDs attached to the PCBs of the antenna nodes. The found pixel locations will then be used to get the spherical coordinates of the antennas with respect to the camera. Finally these spherical coordinates will be transformed to fit to the coordinate system of the ADome itself, by detecting landmarks in the form of fiducial markers which are located at predetermined locations. The methods of recognition of the antennas within using computer vision are discussed, implemented and tested on real and simulated data. The accuracy of finding the antennas on the real data was within 2 pixels from the true location. The methods regarding estimating the location of the antenna with respect to the camera are discussed next. These methods include a distortion estimation and correction, after which each pixel will get there corresponding spherical angles θ and φ. These methods are also tested on simulated and real data, where the accuracy on the real data falls within 0.5 degrees in comparison to the true data. Finally the methods of transforming the spherical angle θ and φ of the antenna with respect to the camera, to the coordinate system of the ADome are discussed. This starts with a method of recognizing fiducial landmarks (landmarks are accurately known reference points), where in this research there is chosen for ArUco fiducials. After this, the location of these landmarks can be used to determine the location and orientation of the camera within the ADome. The method of finding the distances between each of the landmarks and the camera, is discussed and tested and has an accuracy of 2 cm. The method of finding the location of the camera, and the method of finding the orientation of the camera are discussed, however this has not been tested and fully implemented yet. With this location and orientation the location of an antenna can be easily determined. In conclusion, this thesis is a good starting point for designing an Optical Calibration System, which could make determining the location of each of the antennas faster, and more accurate.

The accuracy of a true-RMS detector board based on the Analog Devices LTC5596 is determined by measuring the input power and the output voltage. A number of samples of the output voltage is taken and the mean and standard deviation is shown. These measurements are done for single-tone excitation with a direct connection and over-the-air setup, and for multi-tone excitation with a direct connection. It has been demonstrated that the detector response worsens with over-the-air excitation, resulting in a doubling of the standard deviation in the output voltage compared to a direct connection. With multi-tone excitation, the standard deviation is fifteen times higher than with a direct connection. Additionally, with multi-tone excitation the mean output voltage is lower than with the same input power as single-tone. This discrepancy increases with the amount of tones. A Keysight Advanced Design System simulation is also presented for the three different measurement setups. With the use of a Monte Carlo simulation uncertainty bounds between the function generator and the power detector are made. Furthermore the noise of the power detector is simulated and sources of noise analyzed.

This thesis focuses on improving the readout of the ADome by implementing MCUs at each antenna probe, enabling local sampling and memory storage. The serial communication protocols CAN, SPI and I2C are considered and compared with one another. Ultimately, CAN is decided due to its robustness and simplicity which make the system cheap and ensures that the measurement will not get corrupted during transmission. Moreover, implementations of the new readout protocol are able to obtain measurement data store information at the local MCU. Test setups verification showed that antenna location can be stored and retrieved. Furthermore, the readout protocol is able to acquire multiple samples from the ADC locally.