###### Abstract
There are two main application domains for UWB: (1) infrastructure-free peer-to-peer solutions, such as Apple AirTags and UWB car keys for hands-free access control, and (2) infrastructure-based solutions for reliable location tracking in well-defined areas [19]. An important aspect related to navigation is the requisite accuracy, which varies based on the intended function of the localization system; for instance, in RTLS tracking patients in hospitals, an error of one meter is tolerable, while for tracking in the human body during surgery, an error of one centimeter is unacceptable. A precision of about 50 m in the context of blind people is insufficient for localizing a particular obstacle. The main advantage of UWB is the very precise location tracking within 10 cm with an acceptable position error of 30 cm [20], even in difficult indoor environments. This makes it ideal for providing real-time measurements of distance, direction, and location, while supporting two-way communication, giving it real potential in solutions dedicated to blind people. In the case of radio frequency (RF) signals, which travel at the speed of light, their penetration capabilities offer them an edge over signals reliant on line of sight (LoS), despite the latter showcasing higher accuracy within a few centimeters, as observed in LIDAR systems [21]. At present, there is a lack of standardized indoor location systems, thus demanding the selection of an appropriate solution based on the tracked environment's characteristics and the desired level of accuracy and precision. Location tracking methods can be categorized into two groups: (1) systems that require the active participation of tracked individuals and (2) systems using passive location. The majority of location techniques belong to the category of active systems, which require tags or electronic devices worn by the tracked individual or attached to objects to determine their location. In certain instances, electronic devices may also analyze recorded data and transmit results to an application server housing a location algorithm for further processing. Conversely, in passive localization, position estimation relies on signal variance or video processing. Consequently, the tracked individual lacks electronic devices capable of inferring their position [22]. This paper focuses on the mentioned systems, which consider the primary challenge for radio frequency (RF) in intricate and ever-changing indoor environments marked by noise, multipath propagation, and non-line-of-sight (NLoS) scenarios. Most methodologies for the evaluation of indoor positioning systems (IPSs) in existing research [23; 24; 25; 26] focus on line-of-sight (LoS) scenarios in less noise-prone environments. Therefore, a new approach has to be designed that contains an application that is portable and allows for the collection of different types of measurements and environmental data. These data have to be used to be further analyzed and evaluated in the context of the suitability of UWB-based sensors for people with disabilities to navigate around public buildings. The presented results were obtained by tests that were carried out in various configurations, including fixed positions, using a mobile robot that follows a predefined trajectory equipped with a LIDAR system to serve as a reference point. Possible sources of interference for IPS were also assessed, including NLoS conditions, shadowing, multipath propagation, interference, etc. The aim of this paper and research into the accuracy of beacons that are based on the fusion of BLE and UWB using two-way ranging (TWR) is to analyze and evaluate the influence of various factors on the accuracy of distance measurements. In the case of blind and partially sighted people, it is crucial to be able to guide them accurately in a variety of environments due to the number of possible obstacles along the way.