Radar system calibration is vital for ensuring optimal performance, especially in weather radars that have stringent requirements for co-polarization mismatch. In-field calibration is essential, particularly for mobile weather radars, as environmental conditions can vary between deployments. Traditionally, conventional far-field ranges or airborne systems such as helicopters and aircraft have been used to measure and calibrate radar systems. However, in recent years, Unmanned Aerial Systems (UAS) have emerged as a cost-effective and flexible alternative for antenna measurement and radar calibration. Previous studies have demonstrated the feasibility of using UAS for far-field antenna measurements across various operating frequencies. These works have achieved high accuracy in characterizing and calibrating polarimetric weather radar systems, meeting critical requirements such as co-polarization mismatch below 0.1 dB and cross-polarization isolation below -45 dB. However, existing UAS-based systems are complex to operate, requiring multiple equipment both on the UAS and the ground station. They are primarily limited to one-way transmission from the UAS to the AUT and lack the capability to switch between RX and TX measurements or H- and V-polarization without physical modifications. The objective of this thesis is to develop a lightweight and self-contained front-end system for UAS-based in-situ antenna characterization. This system will eliminate the need for additional RF instruments on the ground, providing remote real-time control to switch between RX and TX modes in both V- and H-polarization. It will also facilitate the transmission and reception of measurement data over long distances, enabling far-field measurements beyond 120 m. The proposed system aims to address the limitations of existing UAS-based calibration systems, offering a sophisticated and accurate solution for measuring the strictest radar systems. By developing a versatile and lightweight front-end system, this research seeks to advance the field of UAS-based antenna characterization and contribute to the improvement of radar calibration techniques.