No abstract

No abstract

With the rise of COVID-19, the sustainability of air transport is a major challenge, as there is limited space in aircraft cabins, resulting in a higher risk of virus transmission. In order to detect possible chains of infection, technology-supported apps are used for social distancing. These COVID-19 applications are based on the display of the received signal strength for distance estimation, which is strongly influenced by the spreading environment due to the signal multipath reception. Therefore, we evaluate the applicability of technology-based social distancing methods in an aircraft cabin environment using a radio propagation simulation based on a three-dimensional aircraft model. We demonstrate the susceptibility to errors of the conventional COVID-19 distance estimation, which can lead to large errors in the determination of distances and to the impracticability of traditional tracing approaches during passenger boarding/deboarding. In the context of the future connected cabin, a robust distance measurement must be implemented to ensure safe travel. Finally, our results can be transferred to similar fields of application, e.g., trains or public transport.

The interconnection of devices, driven by the Internet of Things (IoT), enables a broad variety of smart applications and location-based services. The latter is often realized via transponder based approaches, which actively determine device positions within Wireless Sensor Networks (WSN). In addition, interpreting wireless signal measurements also enables the utilization of radar-like passive localization of objects, further enhancing the capabilities of WSN ranging from environmental mapping to multipath detection. For these approaches, the target objects are not required to hold any device nor to actively participate in the localization process. Instead, the signal delays caused by reflections at objects within the propagation environment are used to localize the object. In this work, we used Ultra-Wide Band (UWB) sensors to measure Channel Impulse Responses (CIRs) within a WSN. Determining an object position based on the CIR can be achieved by formulating an elliptical model. Based on this relation, we propose a CIR environmental mapping (CIR-EM) method, which represents a heatmap generation of the propagation environment based on the CIRs taken from radio communication signals. Along with providing imaging capabilities, this method also allows a more robust localization when compared to state-of-the-art methods. This paper provides a proof-of-concept of passive localization solely based on evaluating radio communication signals by conducting measurement campaigns in an anechoic chamber as a best-case environment. Furthermore, shortcomings due to physical layer limitations when using non-dedicated hardware and signals are investigated. Overall, this work lays a foundation for related research and further evaluation in more application-oriented scenarios.

No abstract