Lab-Based Evaluation of Device-Free Passive Localization Using Multipath Channel Information

Abstract

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.

Multipath-assisted Radio Sensing and Occupancy Detection for Smart In-house Parking in ITS

“…In addition, the family of ellipses can be used to provide a representation of the propagation environment and its reflecting sources by performing an environmental mapping. In [20], we proposed the creation of a heatmap based on the time delays and amplitudes of each CIR value. The resulting continuous value surface of the heatmap is obtained by performing a nearest neighbor interpolation and shown in Fig.…”

“…With multiple CIR measurements between different anchors an unambiguous localization of the reflecting object is also possible. [20]…”

“…1). Furthermore, the UWB CIR can also be used for passive localization of reflecting objects [20,21].…”

Enabling Radio Sensing for Multimodal Intelligent Transportation Systems: From Virtual Testing to Immersive Testbeds

“…For mobile radio evaluation, channel simulation is conventionally realized by applying consolidated statistical channel models [19], which describe predefined scenarios and corresponding channel statistics, inter alia Line-of-Sight probability and path loss [20]. While originally designed to generate inputs for both wireless communication and active radio localization, input data for sensing can hypothetically also be derived, as published works on multipath-enabled radio sensing [21], [22] essentially use the channel coefficients, which are also derived from statistical channel models [20]. Though, as pointed out in [23], exclusive use of spatial statistical channel models is not suitable for sensing applications.…”

“…Consequently, both real-world examination and radio simulation provide the relevant signal properties desired for radio sensing. Among others, the Channel Impulse Response (CIR) of the transmission channel provides essential information for passive sensing [21] and is conventionally provided by raytracing simulation. Based on these inputs, location information and surveillance can be derived and used for ITS in order to provide services and controlling.…”