UWB is a rapidly developing technology characterised by high positioning accuracy, additional data transferability, and communication security. Low costs and energy demand makes it a system that meets the requirements of smart cities (e.g., smart mobility). The analysis of the positioning accuracy of moving objects requires a ground truth. For the UWB system, it should have an accuracy of the order of millimetres. The generated data can be used to minimize the cost and time needed to perform field tests. However, there is no UWB simulators which can consider the variable characteristics of operation along with distance to reflect the operation of real systems. This article presents a 2D UWB simulator for outdoor open-air areas with obstacles and a method of analysing data from the real UWB system under line-of-sight (LOS) and non-line-of-sight conditions. Data are recorded at predefined outdoor reference distances, and by fitting normal distributions to this data and modelling the impact of position changes the real UWB system can be simulated and it makes it possible to create virtual measurements for other locations. Furthermore, the presented method of describing the path using time-dependent equations and obstacles using a set of inequalities allows for reconstructing the real test scenario with moving tags with high accuracy.

The following paper presents advanced methods for evaluating the reliability of ADAS module readings, based on an analysis of the transient supply current. Changes in the transient current waveform occur due to environmental conditions and damage to a module's inner circuitry. Specific deviations in the waveforms may indicate a certain eventeither internal or external. This paper presents how to successfully distinguish certain anomalies using artificial neural network-based classification algorithms without having to interfere with the module's internal circuitry.

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This paper compares two positioning systems, namely ultra-wideband (UWB) based micro-location technology and dead reckoning and a RPLidar based simultaneous localization and mapping (SLAM) solution. This new approach can be used to improve the quality of the positioning system and increase the functionality of advanced driver assistance systems (ADAS). This is achieved by using stationary nodes and UWB tags on the vehicles. Thus, the redundancy of localization can be achieved by this approach, e.g., as a backup to onboard sensors like RPlidar or radar. Additionally, UWB based micro-location allows additional data channels to be used for communication purposes. Furthermore, it is shown that the regular use of correction data increases UWB and dead reckoning accuracy. These correction data can be based on onboard sensors. This shows that it is promising to develop a system that fuses onboard sensors and micro-localization for safety-critical tasks like the platooning of commercial vehicles.

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As a part of the proposed article, the authors presented comprehensive data analysis for movement data that comes from a positioning system based on ultra-wide band (UWB) technology. For purpose of this article, a test was carried out during which the car equipped with cruise control overcame the given path at a speed from 10 km/h to 60 km/h. The obtained motion models (information about position) have been filtered through a series of filters - from fundamentals filters with a variable window (median, moving average, Savitzky-Golay filter), through more complex ones like the Wiener or Kalman filter. As a result, the authors proposed a form of data analysis and filtration depending on the speed of the moving object. In addition, the maximum accuracy that can be obtained for a given traffic model was also determined. The whole research proves that it is possible to use a system based on UWB technology in positioning objects for urban applications - smart city, in industry 4.0 applications as well as for positioning autonomous vehicles in urban applications, such as well as on highways to maintain cohesion of convoys vehicles.

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