There is a noticeable number of studies carried out on both the operational parameters of Global Navigation Satellite System (GNSS) and the satellite signal itself. Researchers look for, inter alia, proven sources of errors affecting the integrity of the satellite signal because this parameter determines the approval of the system’s operational use. It also seems of key importance that the atmospheric conditions, in any area of satellite signal usage, should not be underestimated due to their extensive impact. As the ionospheric refraction seriously limits the operational use of the satellite navigation signal, in this article, the authors attempted to quantify the effect of solar activity (expressed by sunspots) on the signal integrity using fuzzy logic. Fuzzy reasoning is used when information is inaccurate or incomplete and necessitates making decisions under conditions of uncertainty. Thanks to fuzzy sets, there are no obstacles to characterize the degree of intensity of a given phenomenon. In order to look at the problem more broadly, attention was also paid to the tropospheric conditions, and it was verified whether, against the background of cloudiness, precipitation, humidity, pressure and temperature, solar activity affects the integrity to the greatest extent. The integrity measurements from the EGNOS system (PRN120 and PRN126) collected at the monitoring station in Warsaw, Poland in 2014 were used.
The increase in the role of companion robots in everyday life is inevitable, and their safe communication with the infrastructure is one of the fundamental challenges faced by designers. There are many challenges in the robot’s communication with the environment, widely described in the literature on the subject. The threats that scientists believe have the most significant impact on the robot’s communication include denial-of-service (DoS) attacks, satellite signal spoofing, external eavesdropping, spamming, broadcast tampering, and man-in-the-middle attacks. In this article, the authors attempted to identify communication threats in the new robot-to-infrastructure (R2I) model based on available solutions used in transport, e.g., vehicle-to-infrastructure (V2I), taking into account the threats already known affecting the robot’s sensory systems. For this purpose, all threats that may occur in the robot’s communication with the environment were analyzed. Then the risk analysis was carried out, determining, in turn, the likelihood of potential threats occurrence, their consequence, and ability of detection. Finally, specific methods of responding to the occurring threats are proposed, taking into account cybersecurity aspects. A critical new approach is the proposal to use communication and protocols so far dedicated to transport (IEEE 802.11p WAVE, dedicated short-range communications (DSRC)). Then, the companion’s robot should be treated as a pedestrian and some of its sensors as an active smartphone.
This article is a continuation of the authors' study on the ways to ensure safety in the Air Traffic Management (ATM) system. It directly refers to the processes of risk management involving, in particular, risk management in (air) transport. The main aim of this paper is to present and indicate the hazard identification and risk assessment tools that can be used in air transport and to apply one of them for a risk analysis of a specific ATM originating case. This is why, after a short introduction, describing the background of the research as well as literature review, the risk management process as such is characterized. It is shown in a schematic way and its main components are identified. At the same time, from the entire management process, the risk assessment procedure is highlighted as its most crucial part. Then, general hazards identification techniques, risk analysis and assessment tools are described, with an indication that they can also be implemented in air transport, if compatible with ICAO Standards and Recommended Practices (SARPs). In the following part, the process of risk assessment in air transport, based on the Safety Management Manual, using a safety risk tolerability matrix, is characterized. Finally, in this article, an exemplary risk analysis is carried out, focusing on a selected case arising from the ATM field. For the analysed case, safety risk hazards and their possible effects are identified and then assigned to the Intolerable, Tolerable and Acceptable regions. The entire paper is summarized and conclusions are drawn in relation to the publication's main goal. Attention is also paid to the potential causes of appearance of hazards including, first of all, lack of adequate verification procedures, as well as people's competence and last but not the least human errors, being the reason for 70-80% of unwanted transport accidents.
The Internet of Energy is the deployment of IoT technology within energy systems (including distributed power monitoring and measuring points, energy plant sensors, points of distribution) to increase the efficiency of the whole infrastructure while decreasing energy waste. Due to criticality and the extension of the Internet of Energy, it needs an underlying network with vast coverage and high-efficiency parameters. In this paper, we argue that the 5G network is suitable for the Internet of Energy and present a concrete 5G implementation based on Open RAN that may gain in flexibility while reducing costs. In our simulations, we model and validate beamforming mechanism in Open RAN 5G and show that beamforming may achieve high-efficiency parameters that the Internet of Energy requires.
<p>The adverse effects of ionospheric delays limit the positioning accuracy of single-frequency GNSS users. To mitigate these effects, GNSS system providers make several ionospheric delays models available for their global users. For example, the GPS has offered the Klobuchar model from the beginning. More recently, Galileo users can use the NeQuick G model. In the meantime, several independent models available for real-time navigation have emerged. Recent examples are the NTCM (Neustrelitz Total Electron Content Model) correction model provided by the German Aerospace Center (DLR) and real-time global ionosphere maps (RT-GIMs) provided by the National Centre for Space Studies (CNES).</p><p>In this contribution, we evaluate the performance of several global ionospheric delay correction models in SPP mode. We used single-frequency pseudorange data from 12 GNSS stations distributed globally, covering different latitudes for the evaluation. The test data includes GNSS observations from DOY 93/2020 to DOY 80/2021, covering almost one full year of increasing solar activity. We validated the performance of the NTCM-G model driven by the Galileo Az parameters against the Klobuchar, NeQuick 2, NeQuick G, and CNES RT GIMs models. Finally, we compared the results to reference solutions obtained with CODE GIM and also using the ionosphere-free linear combination. We showed that NTCM-G corrections presented accuracy comparable with the NeQuick G model and better than the Klobuchar one.</p>
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