Best Paper Award

    Last Update
  • 02/Dec/2021

Best Paper Award

Accurate Multi-Zone UWB TDOA Localization utilizing Cascaded Wireless Clock Synchronization by Johannes Friedrich, Janis Tiemann and Christian Wietfeld.

Abstract: The high popularity of ultra-wideband technology for accurate indoor positioning in industrial and public spaces has led to a large amount of research in recent years. The focus has mostly been on localization accuracy in small-scale setups with a single localization zone. However, solutions designed for line-of-sight environments are not suitable for many large-scale applications. To overcome this lack of research, we propose novel concepts for precise wireless multi-hop clock synchronization and localization zone selection. By integration into a time-difference-of-arrival-based ultra-wideband localization scheme, continuous cross-spatial positioning in large-scale scenarios is enabled. Validation is carried out in an unprecedented testbed with multiple rooms. We could show that positioning accuracy in multi-room scenarios is up to three times higher when exploiting the proposed concepts compared to the initial accuracy achieved with existing approaches. In addition, we provide an open-source implementation of our real-time localization system.


DOI: 10.1109/IPIN51156.2021.9662537


Received Signal Strength Visible Light Positioning-based Precision Drone Landing System by Sander Bastiaens, Jens Mommerency, Kenneth Deprez, Wout Joseph and David Plets.

Abstract: The next-generation automated inventory management solution revolves around unmanned aerial drones that operate without any human intervention, including during (wireless) charging. As the inductive power transfer system’s efficiency depends on its coil alignment, a precision landing system is required that is lightweight, accurate, and of low-cost. This manuscript demonstrates the potential of received signal strength (RSS) Visible Light Positioning (VLP) with a single photodiode (PD), which is inherently lightweight. A landing system is proposed, in which a PD-equipped drone self-localises with respect to light-emitting diodes (LEDs) that are integrated into the landing zone. The LEDs are furthermore sequentially strung together to cut costs, thereby forming a LED strip. Automated measurements characterise the particular (propagation) challenges and the positioning performance of 3D VLP on a small scale, when mimicking drone landing on a flat surface or in a commercial funnel. For the flat surface, a 50 Hz update rate and a vertical range up to 1 meter, the target of a third quartile VLP-only positioning error bounded by 3.5 cm is attained with multilateration and a 6-element LED strip. The presence of the reflections-inducing drone funnel degrades the positioning performance significantly. However, a sufficient accuracy can still be reached. Both configurations exhibit larger errors close to the landing zone.


DOI: 10.1109/IPIN51156.2021.9662584

POUCET: A Multi-Technology Indoor Positioning Solution for Firefighters and Soldiers by Quentin Vey, François Spies, Baptiste Pestourie, Denis Genon-Catalot, Adrien Van Den Bossche, Thierry Val, Réjane Dalce and Julien Schrive.

Abstract: A novel multi-technology indoor positioning system, Poucet, designed for military and firefighter operations, is introduced in this paper. A mobile agent, wearing a lightweight tracker, is located in real-time during indoor operations through a combination of outdoor stations and indoor beacons dropped by the agent on his way. Beacons and trackers integrate multiple radio positioning technologies, including Global Positioning System, (Long range Radio (LoRa 868MHz and 2.4 GHz), Ultrawide-band (UWB), and altimeters.Poucet’s distributed architecture is presented along with the main features of each of the technologies used. A multi-input fusion algorithm provides continuous and reliable positioning. We report experimental results obtained during benchmarks scenarios conducted by the French National Defense on the presented prototypes.


DOI: 10.1109/IPIN51156.2021.9662587

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