Das CoSA-Seminar findet am 27.02.2023 um 10:30 Uhr in Raum 17-01.02 statt.
Wir haben folgenden Vortrag geplant:
- Marco Cimdins: MA-RTI: Design and Evaluation of a Real-World Multipath-Assisted Device-Free Localization System
Der Vortrag dauert ca. 35 Minuten mit anschließend 10 Minuten Diskussion. Wir freuen uns auf eine rege und aktive Teilnahme.
Die Seminare sind auch auf https://www.th-luebeck.de/cosa/zu finden. Wenn Sie auch einmal einen Vortrag anbieten möchten, kontaktieren Sie uns gerne (fabian.john(at)th-luebeck.de).
Marco Cimdins: MA-RTI: Design and Evaluation of a Real-World Multipath-Assisted Device-Free Localization System
Device-free localization (DFL) systems exploit changes in the radio frequency channel by measuring, for example, the channel impulse response (CIR), to detect and localize obstacles within a target area. However, due to a lack of well-defined interfaces, missing modularization, as well as complex system configuration, it is difficult to deploy DFL systems outside of laboratory setups. This paper focused on the system view and the challenges that come with setting up a DFL system in an indoor environment. We propose MA-RTI, a modular DFL system that is easy to set up, and which utilizes a multipath-assisted (MA) radio-tomographic imaging (RTI) algorithm. To achieve a modular DFL system, we proposed and implemented an architectural model for DFL systems. For minimizing the configuration overhead, we applied a 3D spatial model, that helps in placing the sensors and calculating the required calibration parameters. Therefore, we configured the system solely with idle measurements and a 3D spatial model. We deployed such a DFL system and evaluated it in a real-world office environment with four sensor nodes. The radio technology was ultra-wideband (UWB) and the corresponding signal measurements were CIRs. The DFL system operated with CIRs that provided a sub-nanosecond time-domain resolution. After pre-processing, the update rate was approximately 46 Hz and it provided a localization accuracy of 1.0 m in 50 % of all cases and 1.8 m in 80 % of all cases. MA fingerprinting approaches lead to higher localization accuracy, but require a labor-intensive training phase.