The CoSA seminar will be held on February, 27th 2023 at 10:30am in room 17-01.02.
We have planned the following presentation:
- Marco Cimdins: MA-RTI: Design and Evaluation of a Real-World Multipath-Assisted Device-Free Localization System
The presentation will last approximately 35 minutes followed by 10 minutes of discussion. We look forward to a lively and active participation.
The seminars can also be found at https://www.th-luebeck.de/cosa/. If you would like to offer a talk as well, please feel free to contact us (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.