User Localization using RF Sensing: A Performance comparison between LIS and mm Wave Radars

Cristian J. Vaca-Rubio; Dariush Salami; Petar Popovski; Elisabeth de Carvalho; Zheng Hua Tan; Stephan Sigg

doi:10.48550/arXiv.2205.10321

User Localization using RF Sensing: A Performance comparison between LIS and mm Wave Radars

Cristian J. Vaca-Rubio, Dariush Salami, Petar Popovski, Elisabeth de Carvalho, Zheng Hua Tan, Stephan Sigg

Tutkimustuotos: Artikkeli kirjassa/konferenssijulkaisussa › Conference contribution › Scientific › vertaisarvioitu

Abstrakti

Since electromagnetic signals are omnipresent, Radio Frequency (RF)-sensing 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-sensing, namely sensing through Large Intelligent Surfaces (LISs) and mmWave 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 mmWave radar achieves 0.71 Intersection Over Union (IOU) and 3cm error for bounding boxes, while LIS has 0.56 IOU and 10cm distance error. Although the radar outperforms the LIS in terms of accuracy, LIS features additional applications in communication in addition to sensing scenarios.

Alkuperäiskieli	Englanti
Otsikko	30th European Signal Processing Conference, EUSIPCO 2022 - Proceedings
Kustantaja	European Signal Processing Conference (EUSIPCO)
Sivut	1916-1920
Sivumäärä	5
ISBN (elektroninen)	9789082797091
DOI - pysyväislinkit	https://doi.org/10.48550/arXiv.2205.10321
Tila	Julkaistu - 2022
OKM-julkaisutyyppi	A4 Artikkeli konferenssijulkaisuussa
Tapahtuma	European Signal Processing Conference - Belgrade, Serbia Kesto: 29 elok. 2022 → 2 syysk. 2022 Konferenssinumero: 30 https://2022.eusipco.org/

Julkaisusarja

Nimi	European Signal Processing Conference
Vuosikerta	2022-August
ISSN (painettu)	2219-5491

Conference

Conference	European Signal Processing Conference
Lyhennettä	EUSIPCO
Maa/Alue	Serbia
Kaupunki	Belgrade
Ajanjakso	29/08/2022 → 02/09/2022
www-osoite	https://2022.eusipco.org/

Pääsy asiakirjaan

10.48550/arXiv.2205.10321

https://ieeexplore.ieee.org/document/9909583

OpenUrl-saatavuus

Koko teksti

Muut tiedostot ja linkit

Linkki julkaisuun Scopuksessa

WINDMILL: Integrating Wireless Communication ENgineering and MachIne Learning
Tirkkonen, O., Salami, D., Sigg, S. & Kazemi, P.
01/01/2019 → 30/06/2023
Projekti: EU: MC

Science-IT
Mikko Hakala (Manager)
Perustieteiden korkeakoulu
Laitteistot/tilat: Facility

Siteeraa tätä

Vaca-Rubio, C. J., Salami, D., Popovski, P., de Carvalho, E., Tan, Z. H., & Sigg, S. (2022). User Localization using RF Sensing: A Performance comparison between LIS and mm Wave Radars. teoksessa 30th European Signal Processing Conference, EUSIPCO 2022 - Proceedings (Sivut 1916-1920). (European Signal Processing Conference; Vuosikerta 2022-August). European Signal Processing Conference (EUSIPCO). https://doi.org/10.48550/arXiv.2205.10321

@inproceedings{c68031effcdf4481b3639fdf8f33c8fb,

title = "User Localization using RF Sensing: A Performance comparison between LIS and mm Wave Radars",

abstract = "Since electromagnetic signals are omnipresent, Radio Frequency (RF)-sensing 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-sensing, namely sensing through Large Intelligent Surfaces (LISs) and mmWave 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 mmWave radar achieves 0.71 Intersection Over Union (IOU) and 3cm error for bounding boxes, while LIS has 0.56 IOU and 10cm distance error. Although the radar outperforms the LIS in terms of accuracy, LIS features additional applications in communication in addition to sensing scenarios.",

keywords = "FMCW, LIS, machine learning, mmWave, radar, Sensing",

author = "Vaca-Rubio, {Cristian J.} and Dariush Salami and Petar Popovski and {de Carvalho}, Elisabeth and Tan, {Zheng Hua} and Stephan Sigg",

note = "Funding Information: This project has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie Grant agreement No, 813999. Publisher Copyright: {\textcopyright} 2022 European Signal Processing Conference, EUSIPCO. All rights reserved. | openaire: EC/H2020/813999/EU//WINDMILL; European Signal Processing Conference, EUSIPCO ; Conference date: 29-08-2022 Through 02-09-2022",

year = "2022",

doi = "10.48550/arXiv.2205.10321",

language = "English",

series = "European Signal Processing Conference",

publisher = "European Signal Processing Conference (EUSIPCO)",

pages = "1916--1920",

booktitle = "30th European Signal Processing Conference, EUSIPCO 2022 - Proceedings",

url = "https://2022.eusipco.org/",

}

Vaca-Rubio, CJ, Salami, D, Popovski, P, de Carvalho, E, Tan, ZH & Sigg, S 2022, User Localization using RF Sensing: A Performance comparison between LIS and mm Wave Radars. julkaisussa 30th European Signal Processing Conference, EUSIPCO 2022 - Proceedings. European Signal Processing Conference, Vuosikerta 2022-August, European Signal Processing Conference (EUSIPCO), Sivut 1916-1920, European Signal Processing Conference, Belgrade, Serbia, 29/08/2022. https://doi.org/10.48550/arXiv.2205.10321

User Localization using RF Sensing : A Performance comparison between LIS and mm Wave Radars. / Vaca-Rubio, Cristian J.; Salami, Dariush; Popovski, Petar et al.

30th European Signal Processing Conference, EUSIPCO 2022 - Proceedings. European Signal Processing Conference (EUSIPCO), 2022. s. 1916-1920 (European Signal Processing Conference; Vuosikerta 2022-August).

Tutkimustuotos: Artikkeli kirjassa/konferenssijulkaisussa › Conference contribution › Scientific › vertaisarvioitu

TY - GEN

T1 - User Localization using RF Sensing

T2 - European Signal Processing Conference

AU - Vaca-Rubio, Cristian J.

AU - Salami, Dariush

AU - Popovski, Petar

AU - de Carvalho, Elisabeth

AU - Tan, Zheng Hua

AU - Sigg, Stephan

N1 - Conference code: 30

PY - 2022

Y1 - 2022

N2 - Since electromagnetic signals are omnipresent, Radio Frequency (RF)-sensing 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-sensing, namely sensing through Large Intelligent Surfaces (LISs) and mmWave 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 mmWave radar achieves 0.71 Intersection Over Union (IOU) and 3cm error for bounding boxes, while LIS has 0.56 IOU and 10cm distance error. Although the radar outperforms the LIS in terms of accuracy, LIS features additional applications in communication in addition to sensing scenarios.

AB - Since electromagnetic signals are omnipresent, Radio Frequency (RF)-sensing 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-sensing, namely sensing through Large Intelligent Surfaces (LISs) and mmWave 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 mmWave radar achieves 0.71 Intersection Over Union (IOU) and 3cm error for bounding boxes, while LIS has 0.56 IOU and 10cm distance error. Although the radar outperforms the LIS in terms of accuracy, LIS features additional applications in communication in addition to sensing scenarios.

KW - FMCW

KW - LIS

KW - machine learning

KW - mmWave

KW - radar

KW - Sensing

UR - http://www.scopus.com/inward/record.url?scp=85141011380&partnerID=8YFLogxK

U2 - 10.48550/arXiv.2205.10321

DO - 10.48550/arXiv.2205.10321

M3 - Conference contribution

AN - SCOPUS:85141011380

T3 - European Signal Processing Conference

SP - 1916

EP - 1920

BT - 30th European Signal Processing Conference, EUSIPCO 2022 - Proceedings

PB - European Signal Processing Conference (EUSIPCO)

Y2 - 29 August 2022 through 2 September 2022

ER -

Vaca-Rubio CJ, Salami D, Popovski P, de Carvalho E, Tan ZH, Sigg S. User Localization using RF Sensing: A Performance comparison between LIS and mm Wave Radars. julkaisussa 30th European Signal Processing Conference, EUSIPCO 2022 - Proceedings. European Signal Processing Conference (EUSIPCO). 2022. s. 1916-1920. (European Signal Processing Conference). doi: 10.48550/arXiv.2205.10321

User Localization using RF Sensing: A Performance comparison between LIS and mm Wave Radars

Abstrakti

Julkaisusarja

Conference

Pääsy asiakirjaan

OpenUrl-saatavuus

Muut tiedostot ja linkit

Sormenjälki

Projektit

WINDMILL: Integrating Wireless Communication ENgineering and MachIne Learning

Laitteet

Science-IT

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