## 2 Architecture of the Tethered Hexacopter System
### UWB Positioning System  
The local positioning system was developed using ultra-wideband (UWB) technology and served as an integral component within the relative positioning algorithm. The UWB-based positioning system utilized in the following application consisted of eight anchors, which were organized as depicted in Figure 8. To accurately estimate position, this system employed a technique known as later, which relies on measuring distances. It used two types of ranging devices: anchors placed stationarily at the landing pad, and tags mounted on the unmanned aerial vehicles (UAVs). By integrating these distance measurements with established anchor positions, precise calculations could be made to determine each tag's specific location. To address the specific requirements of fast-moving flying objects and the integration of positioning systems, a specialized structure for the positioning algorithm was implemented. Three distinct stages could be distinguished in the aforementioned algorithm, as illustrated in Figure 9.  
One of the primary concerns in the mentioned application revolved around the possibility of the UAV exceeding the serviceable range of measurement in the UWB devices. In such cases, some or all of the distance measurements may have become unavailable. Another issue arose when the distance between the measuring devices became too close to the maximum range that could be measured, resulting in intermittent distance measurements and highly distorted values. Furthermore, obstacles like cables, trees, the UAV itself, humans, or terrain could obstruct the radio signal, affecting distance measurements. To overcome these challenges, the UWB-based positioning algorithm incorporated an evaluation of the distance measurement quality in its initial stage. Figure 8: Layout of the UWB system. When the first stage finished, every distance measurement was classified into one of three categories: measurement taken without any disturbances, measurement affected by poor conditions, or non-usable measurement. The quality of each measurement was assessed by utilizing the update flag and the signal-to-noise ratio (SNR) value, which were transmitted within the data frame by the UWB modules used in the positioning system. During the initial step, the update flag was carefully analyzed. In the update flag, a dedicated bit was assigned to each measurement, with a value of 0 indicating the inability to obtain the measurement between a specific anchor and tag. Subsequently, the SNR parameter was evaluated. Measurements captured under unfavorable conditions were determined by evaluating the ratio between the signal-to-noise ratio (SNR) and the distance. If this ratio fell below a predefined threshold, the measurement was considered to have been taken in less-than-optimal conditions. Measurements with an SNR value lower than another threshold were considered non-usable. During testing, the threshold of the SNR was defined at \(-18\) dBm. It is important to note that when the SNR value decreased below \(-20\) dBm, the measurements tended to be inconsistent and significantly less accurate [32; 33]. To address this phenomenon, the threshold was intentionally set 2 dBm higher than the observed boundary. This adjustment helped mitigate the impact of the discontinuity and accuracy issues caused by low SNR values. By setting the threshold at \(-18\) dBm, positioning ranges exceeding 35 m could be achieved while simultaneously meeting the primary objective to prevent substantial error spikes in the results, as they had the potential to compromise flight stability. The second stage of the algorithm heavily relied on the evaluated distance measurements, which served as vital inputs for the robust extended Kalman filter. This filter played a crucial role in processing and incorporating measurements to estimate the tag's coordinates accurately. This adaptive filter could effectively handle varying numbers of inputs in subsequent steps, ensuring the reliable estimation of the tag's coordinates.