Paper Title

Abstract - Unmanned ground vehicles (UGV) have great potential in military and civilian applications and have become the focus of research in many countries. Upgrading the UGV to an autonomous vehicle additionally increases reliability and efficiency in various applications. One of the basic functions of the autonomous UGV is "Follow me", where the UGV follows a person or another vehicle (object). The basic sensor used to determine the position of the UGV in relation to the object is the ultra-wideband sensor (UWB). UWB wireless technology has many advantages, such as high precision and transmission rate. However, the main disadvantage of these sensors is the appearance of noise as a consequence of multi-sensor interference and noise in the sensor. In this paper, the possibility of reducing noise in determining the distance and angle between the UGV and the tag located on the object is discussed. State of the art algorithms implemented in the MATLAB and Python software packages were used to reduce the impact of noise, taking into account the computational requirements and the implementation of algorithms in real systems. Algorithms were applied to real signals, with special attention to signals that represent the angle of the UGV and the object, which contain significantly more noise and whose reliability is very important for keeping UGV in the right direction. Also, the influence of obstacles, which can be found in real situations, on real signals was considered. The results obtained by applying the algorithms provide stability and possible application for the ‘’follow me’’ function of UGV in real conditions.