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Abstract
Since electromagnetic signals are omnipresent. Radio Frequency (RF)-seiisting has the potential to become a universal sensing mechanism with applications in localization, smart-home. retail, gesture recognition, intrusion detection, etc. Two emerging technologies in RF-seusing, namely sensing through Large Intelligent Surfaces (LISs) and mm Wave Frequency-Modulated Continuous-Wave (FMCW) radars, have been successfully applied to a wide range of applications. In this work, we compare LIS and mmWave radars for localization in real-world and simulated environments. In our experiments, the mm Wave radar achieves 0.71 Intersection Over Union (IOU) and 3cm error for bounding hoxes. while MS has 0,56 IOU and tflcni distance error. Although the radar outperforms the LIS hi terms of accuracy. LIS features additional applications in communication in addition to sensing scenarios.
Original language | English |
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Title of host publication | 30th European Signal Processing Conference, EUSIPCO 2022 - Proceedings |
Publisher | European Signal Processing Conference (EUSIPCO) |
Pages | 1916-1920 |
Number of pages | 5 |
ISBN (Electronic) | 9789082797091 |
DOIs | |
Publication status | Published - 2022 |
MoE publication type | A4 Article in a conference publication |
Event | European Signal Processing Conference - Belgrade, Serbia Duration: 29 Aug 2022 → 2 Sep 2022 Conference number: 30 https://2022.eusipco.org/ |
Publication series
Name | European Signal Processing Conference |
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Volume | 2022-August |
ISSN (Print) | 2219-5491 |
Conference
Conference | European Signal Processing Conference |
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Abbreviated title | EUSIPCO |
Country/Territory | Serbia |
City | Belgrade |
Period | 29/08/2022 → 02/09/2022 |
Internet address |
Keywords
- FMCW
- LIS
- machine learning
- mmWave
- radar
- Sensing
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Dive into the research topics of 'User Localization using RF Sensing: A Performance comparison between LIS and mm Wave Radars'. Together they form a unique fingerprint.Projects
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WINDMILL: Integrating Wireless Communication ENgineering and MachIne Learning
Tirkkonen, O., Kazemi, P., Sigg, S. & Salami, D.
01/01/2019 → 30/06/2023
Project: EU: MC