ORACLE: Occlusion-Resilient and Self-Calibrating mmWave Radar Network for People Tracking

Millimeter wave (mmWave) radar sensors are emerging as valid alternatives to cameras for the pervasive contactless monitoring of people in indoor spaces. However, commercial mmWave radars feature a limited range (up to 6-8 m) and are subject to occlusion, which may constitute a significant drawback...

Full description

Saved in:
Bibliographic Details
Published inIEEE sensors journal Vol. 24; no. 3; p. 1
Main Authors Canil, Marco, Pegoraro, Jacopo, Shastri, Anish, Casari, Paolo, Rossi, Michele
Format Journal Article
LanguageEnglish
Published New York IEEE 01.02.2024
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Algorithms
Indoor sensing
Millimeter wave communication
Millimeter waves
mmWave radar network
Moving targets
Occlusion
Orientation
people tracking
Radar
Radar equipment
radar fusion
Radar networks
Radar tracking
self calibration
Sensor fusion
Sensors
Spaceborne radar
Target tracking
Tracking errors
Online AccessGet full text

Cover

Abstract Millimeter wave (mmWave) radar sensors are emerging as valid alternatives to cameras for the pervasive contactless monitoring of people in indoor spaces. However, commercial mmWave radars feature a limited range (up to 6-8 m) and are subject to occlusion, which may constitute a significant drawback in large, crowded rooms characterized by a challenging multipath environment. Thus, covering large indoor spaces requires multiple radars with known relative position and orientation and algorithms to combine their outputs. In this work, we present ORACLE, an autonomous system that ( i ) integrates automatic relative position and orientation estimation from multiple radar devices by exploiting the trajectories of people moving freely in the radars' common fields of view, and ( ii ) fuses the tracking information from multiple radars to obtain a unified tracking among all sensors. Our implementation and experimental evaluation of ORACLE results in median errors of 0.12 m and 0.03° for radars location and orientation estimates, respectively. Fused tracking improves the mean target tracking accuracy by 27%, and the mean tracking error is 23 cm in the most challenging case of 3 moving targets. Finally, ORACLE does not show significant performance reduction when the fusion rate is reduced to up to 1/5 of the frame rate of the single radar sensors, thus being amenable to a lightweight implementation on a resource-constrained fusion center.
AbstractList Millimeter wave (mmWave) radar sensors are emerging as valid alternatives to cameras for the pervasive contactless monitoring of people in indoor spaces. However, commercial mmWave radars feature a limited range (up to 6-8 m) and are subject to occlusion, which may constitute a significant drawback in large, crowded rooms characterized by a challenging multipath environment. Thus, covering large indoor spaces requires multiple radars with known relative position and orientation and algorithms to combine their outputs. In this work, we present ORACLE, an autonomous system that ( i ) integrates automatic relative position and orientation estimation from multiple radar devices by exploiting the trajectories of people moving freely in the radars' common fields of view, and ( ii ) fuses the tracking information from multiple radars to obtain a unified tracking among all sensors. Our implementation and experimental evaluation of ORACLE results in median errors of 0.12 m and 0.03° for radars location and orientation estimates, respectively. Fused tracking improves the mean target tracking accuracy by 27%, and the mean tracking error is 23 cm in the most challenging case of 3 moving targets. Finally, ORACLE does not show significant performance reduction when the fusion rate is reduced to up to 1/5 of the frame rate of the single radar sensors, thus being amenable to a lightweight implementation on a resource-constrained fusion center.
Millimeter-wave (mmWave) radar sensors are emerging as valid alternatives to cameras for the pervasive contactless monitoring of people in indoor spaces. However, commercial mmWave radars feature a limited range (up to 6–8 m) and are subject to occlusion, which may constitute a significant drawback in large, crowded rooms characterized by a challenging multipath environment. Thus, covering large indoor spaces requires multiple radars with known relative position and orientation and algorithms to combine their outputs. In this work, we present ORACLE, an autonomous system that: 1) integrates automatic relative position and orientation estimation from multiple radar devices by exploiting the trajectories of people moving freely in the radars’ common fields of view and 2) fuses the tracking information from multiple radars to obtain a unified tracking among all sensors. Our implementation and experimental evaluation of ORACLE results in median errors of 0.12 m and 0.03° for radar location and orientation estimates, respectively. Fused tracking improves the mean target tracking accuracy by 27% and the mean tracking error is 23 cm in the most challenging case of three moving targets. Finally, ORACLE does not show significant performance reduction when the fusion rate is reduced to up to 1/5 of the frame rate of the single radar sensors, thus being amenable to a lightweight implementation on a resource-constrained fusion center (FC).
Author Rossi, Michele
Pegoraro, Jacopo
Casari, Paolo
Shastri, Anish
Canil, Marco
Author_xml – sequence: 1
  givenname: Marco
  orcidid: 0000-0001-8037-7497
  surname: Canil
  fullname: Canil, Marco
  organization: Department of Information Engineering, University of Padova, Padova, Italy
– sequence: 2
  givenname: Jacopo
  surname: Pegoraro
  fullname: Pegoraro, Jacopo
  organization: Department of Information Engineering, University of Padova, Padova, Italy
– sequence: 3
  givenname: Anish
  surname: Shastri
  fullname: Shastri, Anish
  organization: Department of Information Engineering and Computer Science, University of Trento, Povo, Italy
– sequence: 4
  givenname: Paolo
  orcidid: 0000-0002-6401-1660
  surname: Casari
  fullname: Casari, Paolo
  organization: Department of Information Engineering and Computer Science, University of Trento, Povo, Italy
– sequence: 5
  givenname: Michele
  orcidid: 0000-0003-1121-324X
  surname: Rossi
  fullname: Rossi, Michele
  organization: Department of Information Engineering, University of Padova, Padova, Italy
BookMark eNp9kE1PAjEURRujiYD-ABMXTVwPtvMobd0Rgl8hYACjriad8sYUhil2Bo3_3pnAwrhw9d7innuT0ybHhS-QkAvOupwzff04H026MYuhCwAa-vqItLgQKuKyp46bH1jUA_l6StpluWKMaylki7xNZ4PheHRDp9bmu9L5Ipph6XKHRUVNsaRzzLNoaHKXBlO54p1uNi_mE-nMLE2gE6y-fFjTzAf6hH6bI10EY9d18IycZCYv8fxwO-T5drQY3kfj6d3DcDCOLICsIlxaLXk_VShSAESdxYopUMiMMtZCtkQlAQWzAkUv5plMuUi5TCWmmRAWOuRq37sN_mOHZZWs_C4U9WQS69qIElr36xTfp2zwZRkwS7bBbUz4TjhLGoNJYzBpDCYHgzUj_zDWVbUEX1TBuPxf8nJPOkT8tQS9WPUF_ABx1oBV
CODEN ISJEAZ
CitedBy_id crossref_primary_10_1109_OJSP_2024_3444709
Cites_doi 10.1109/TITS.2005.858784
10.1109/MSP.2016.2628914
10.1109/ACCESS.2017.2667720
10.1109/COMST.2022.3177305
10.3390/s20061599
10.1109/RadarConf2147009.2021.9454972
10.1145/3563357.3564078
10.1109/IRS.2012.6233325
10.1109/DCOSS.2019.00028
10.1002/nav.20053
10.1109/MCS.2009.934469
10.23919/EuRAD50154.2022.9784533
10.1109/RWS.2007.351749
10.1109/ACCESS.2021.3083980
10.1109/JSTSP.2021.3138632
10.1109/7.625124
10.2307/1271436
10.1109/RadarConf2248738.2022.9764173
10.1145/3565474.3569068
10.1109/62.821657
10.1109/RADAR.2016.7485236
10.1109/ICASSP.2019.8682406
10.1609/aaai.v34i01.5430
10.1109/MAES.2019.2933971
10.1115/1.3662552
10.1109/MC.2019.2913626
10.1109/GLOBECOM46510.2021.9685213
10.1109/WCL.2013.120513.130760
10.1109/JBHI.2023.3237077
10.1109/JSEN.2021.3117707
10.1109/RadarConf2043947.2020.9266697
10.1145/3349624.3356768
10.1109/INFOCOMWKSHPS51825.2021.9484562
10.1109/TAC.1979.1102177
ContentType Journal Article
Copyright Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2024
Copyright_xml – notice: Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2024
DBID 97E
ESBDL
RIA
RIE
AAYXX
CITATION
7SP
7U5
8FD
L7M
DOI 10.1109/JSEN.2023.3339369
DatabaseName IEEE All-Society Periodicals Package (ASPP) 2005–Present
IEEE Xplore Open Access Journals
IEEE All-Society Periodicals Package (ASPP) 1998–Present
IEEE Electronic Library (IEL)
CrossRef
Electronics & Communications Abstracts
Solid State and Superconductivity Abstracts
Technology Research Database
Advanced Technologies Database with Aerospace
DatabaseTitle CrossRef
Solid State and Superconductivity Abstracts
Technology Research Database
Advanced Technologies Database with Aerospace
Electronics & Communications Abstracts
DatabaseTitleList
Solid State and Superconductivity Abstracts
Database_xml – sequence: 1
  dbid: RIE
  name: IEEE Electronic Library (IEL)
  url: https://proxy.k.utb.cz/login?url=https://ieeexplore.ieee.org/
  sourceTypes: Publisher
DeliveryMethod fulltext_linktorsrc
Discipline Geography
Engineering
EISSN 1558-1748
EndPage 1
ExternalDocumentID 10_1109_JSEN_2023_3339369
10342865
Genre orig-research
GrantInformation_xml – fundername: Horizon 2020 Framework Programme
  grantid: 861222
  funderid: 10.13039/100010661
GroupedDBID -~X
0R~
29I
4.4
5GY
6IK
97E
AAJGR
AARMG
AASAJ
AAWTH
ABAZT
ABQJQ
ABVLG
ACGFO
ACGFS
ACIWK
AENEX
AGQYO
AHBIQ
AJQPL
AKJIK
AKQYR
ALMA_UNASSIGNED_HOLDINGS
ATWAV
BEFXN
BFFAM
BGNUA
BKEBE
BPEOZ
CS3
EBS
ESBDL
F5P
HZ~
IFIPE
IPLJI
JAVBF
LAI
M43
O9-
OCL
P2P
RIA
RIE
RNS
TWZ
AAYXX
CITATION
7SP
7U5
8FD
L7M
ID FETCH-LOGICAL-c337t-edc9716b8e5b33ee9f280838e0a8acc3fde873e50c5e5421f7b15b17b7ebf55c3
IEDL.DBID RIE
ISSN 1530-437X
IngestDate Mon Jun 30 10:12:37 EDT 2025
Tue Jul 01 04:27:22 EDT 2025
Thu Apr 24 23:03:25 EDT 2025
Wed Aug 27 02:24:50 EDT 2025
IsDoiOpenAccess true
IsOpenAccess true
IsPeerReviewed true
IsScholarly true
Issue 3
Language English
License https://creativecommons.org/licenses/by/4.0/legalcode
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-c337t-edc9716b8e5b33ee9f280838e0a8acc3fde873e50c5e5421f7b15b17b7ebf55c3
Notes ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ORCID 0000-0001-8037-7497
0000-0002-6401-1660
0000-0003-1121-324X
0000-0002-9352-5417
0000-0003-3555-5666
OpenAccessLink https://proxy.k.utb.cz/login?url=https://ieeexplore.ieee.org/document/10342865
PQID 2920285996
PQPubID 75733
PageCount 1
ParticipantIDs proquest_journals_2920285996
ieee_primary_10342865
crossref_primary_10_1109_JSEN_2023_3339369
crossref_citationtrail_10_1109_JSEN_2023_3339369
ProviderPackageCode CITATION
AAYXX
PublicationCentury 2000
PublicationDate 2024-02-01
PublicationDateYYYYMMDD 2024-02-01
PublicationDate_xml – month: 02
  year: 2024
  text: 2024-02-01
  day: 01
PublicationDecade 2020
PublicationPlace New York
PublicationPlace_xml – name: New York
PublicationTitle IEEE sensors journal
PublicationTitleAbbrev JSEN
PublicationYear 2024
Publisher IEEE
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher_xml – name: IEEE
– name: The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
References ref13
ref35
ref12
ref34
ref14
Ester (ref30)
ref36
ref31
ref11
ref10
ref32
ref2
ref1
ref17
ref16
ref38
ref19
Chernyak (ref15) 1998
ref18
ref24
ref23
ref26
ref25
ref20
ref22
ref21
ref28
ref27
ref29
ref8
ref7
ref9
ref4
ref3
ref6
ref5
Sorkine-Hornung (ref33) 2017; 1
Bernardin (ref37); 90
References_xml – ident: ref21
  doi: 10.1109/TITS.2005.858784
– ident: ref27
  doi: 10.1109/MSP.2016.2628914
– ident: ref28
  doi: 10.1109/ACCESS.2017.2667720
– ident: ref3
  doi: 10.1109/COMST.2022.3177305
– ident: ref17
  doi: 10.3390/s20061599
– ident: ref24
  doi: 10.1109/RadarConf2147009.2021.9454972
– ident: ref12
  doi: 10.1145/3563357.3564078
– ident: ref19
  doi: 10.1109/IRS.2012.6233325
– ident: ref5
  doi: 10.1109/DCOSS.2019.00028
– ident: ref34
  doi: 10.1002/nav.20053
– volume: 1
  start-page: 1
  issue: 1
  year: 2017
  ident: ref33
  article-title: Least-squares rigid motion using SVD
  publication-title: Computing
– ident: ref32
  doi: 10.1109/MCS.2009.934469
– ident: ref22
  doi: 10.23919/EuRAD50154.2022.9784533
– volume: 90
  start-page: 1
  issue: 91
  volume-title: Proc. 6th IEEE Int. Workshop Vis. Surveill.
  ident: ref37
  article-title: Multiple object tracking performance metrics and evaluation in a smart room environment
– ident: ref20
  doi: 10.1109/RWS.2007.351749
– ident: ref4
  doi: 10.1109/ACCESS.2021.3083980
– ident: ref6
  doi: 10.1109/JSTSP.2021.3138632
– start-page: 1
  volume-title: Proc. ACM Conf. Knowl. Discovery Data Mining (KDD)
  ident: ref30
  article-title: A density-based algorithm for discovering clusters in large spatial databases with noise
– ident: ref35
  doi: 10.1109/7.625124
– ident: ref36
  doi: 10.2307/1271436
– ident: ref13
  doi: 10.1109/RadarConf2248738.2022.9764173
– ident: ref14
  doi: 10.1145/3565474.3569068
– ident: ref29
  doi: 10.1109/62.821657
– ident: ref16
  doi: 10.1109/RADAR.2016.7485236
– ident: ref23
  doi: 10.1109/ICASSP.2019.8682406
– ident: ref25
  doi: 10.1609/aaai.v34i01.5430
– ident: ref1
  doi: 10.1109/MAES.2019.2933971
– volume-title: Fundamentals of Multisite Radar Systems: Multistatic Radars and Multistatic Radar Systems
  year: 1998
  ident: ref15
– ident: ref31
  doi: 10.1115/1.3662552
– ident: ref2
  doi: 10.1109/MC.2019.2913626
– ident: ref9
  doi: 10.1109/GLOBECOM46510.2021.9685213
– ident: ref18
  doi: 10.1109/WCL.2013.120513.130760
– ident: ref8
  doi: 10.1109/JBHI.2023.3237077
– ident: ref11
  doi: 10.1109/JSEN.2021.3117707
– ident: ref26
  doi: 10.1109/RadarConf2043947.2020.9266697
– ident: ref7
  doi: 10.1145/3349624.3356768
– ident: ref10
  doi: 10.1109/INFOCOMWKSHPS51825.2021.9484562
– ident: ref38
  doi: 10.1109/TAC.1979.1102177
SSID ssj0019757
Score 2.4000947
Snippet Millimeter wave (mmWave) radar sensors are emerging as valid alternatives to cameras for the pervasive contactless monitoring of people in indoor spaces....
Millimeter-wave (mmWave) radar sensors are emerging as valid alternatives to cameras for the pervasive contactless monitoring of people in indoor spaces....
SourceID proquest
crossref
ieee
SourceType Aggregation Database
Enrichment Source
Index Database
Publisher
StartPage 1
SubjectTerms Algorithms
Indoor sensing
Millimeter wave communication
Millimeter waves
mmWave radar network
Moving targets
Occlusion
Orientation
people tracking
Radar
Radar equipment
radar fusion
Radar networks
Radar tracking
self calibration
Sensor fusion
Sensors
Spaceborne radar
Target tracking
Tracking errors
Title ORACLE: Occlusion-Resilient and Self-Calibrating mmWave Radar Network for People Tracking
URI https://ieeexplore.ieee.org/document/10342865
https://www.proquest.com/docview/2920285996
Volume 24
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
link http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwjV1BaxQxFA62F_WgtVa62koOnoSMmU2yyXgrZUspupWtxfU05CVvtLidSrsr6K9vXma21IribRgSCPO9TF6S930fY69kU0F0zVBAhU5oAC-8dF7QO1saF5Ui7vD7yejwVB_NzKwnq2cuDCLm4jMs6DHf5ceLsKSjsjTDlSYm5RpbSzu3jqx1c2VQ2SzrmWawFFrZWX-FWcrqzdHJeFKQT3ihlCIHu98Woeyq8sevOK8vB4_ZZDWyrqzkW7FcQBF-3RFt_O-hb7BHfabJ97rQeMLuYbvJHt7SH9xk93sL9K8_n7LPx9O9_Xfjt_w4hPmSztDEFK_O5sSX5L6N_ATnjSAqF1DQtF_4-fkn_wP51Ed_ySddOTlPOTD_kKvSeVoGAx3Eb7HTg_HH_UPR-y6IoJRdCIyBhKXAoQGlEKtm6FKm5lB650NQTURnFRoZDBo9LBsLpYHSgkVojAnqGVtvL1rcZjx9a-8QHAQXdAALUWEc6ZEGL4exqQZMroCoQy9KTt4Y8zpvTmRVE3Y1YVf32A3Y65su3ztFjn813iIsbjXsYBiwnRXcdT9pr2oy7iI9v2r0_C_dXrAHqYnuqrZ32Pricom7KSlZwMscjNcant3A
linkProvider IEEE
linkToHtml http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwjV3PTxQxFG4UD-gBFSEuoPbgyaRjZ9tuO94IWbLiMpgF4nqa9McbNS4DgV0S-evt68wS1Gi8TSZt0szX9r1p3_d9hLzmdeGCqfvMFWCYdM4yy41l-E7nygQhkDt8WA5Gp_JgqqYdWT1xYQAgFZ9Bho_pLj-c-wUelcUVLiQyKe-TBzHwq7yla91eGhQ6CXvGNcyZFHraXWLmvHh7cDwsM3QKz4QQ6GH3SxhKvip_bMYpwuw_JuVybG1hyfdsMXeZv_lNtvG_B_-ErHW5Jt1tJ8dTcg-adfLojgLhOlntTNC__nhGPh9NdvfGw3f0yPvZAk_R2ASuvs2QMUltE-gxzGqGZC6H06b5Qs_OPtlroBMb7CUt24JyGrNg-jHVpdMYCD0exW-Q0_3hyd6Idc4LzAuh5wyCR2kpZ0A5IQCKum9irmaAW2O9F3UAowUo7hUo2c9r7XLlcu00uFopLzbJSnPewHNC47e2Bpxx3njpnXZBQBjIgXSW90Nd9AhfAlH5TpYc3TFmVfo94UWF2FWIXdVh1yNvbrtctJoc_2q8gVjcadjC0CM7S7irbtleVWjdhYp-xWDrL91ekdXRyeG4Gr8vP2yTh7G5bGu4d8jK_HIBL2KKMncv08T8CdWW4Qk
openUrl ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=ORACLE%3A+Occlusion-Resilient+and+Self-Calibrating+mmWave+Radar+Network+for+People+Tracking&rft.jtitle=IEEE+sensors+journal&rft.au=Canil%2C+Marco&rft.au=Pegoraro%2C+Jacopo&rft.au=Shastri%2C+Anish&rft.au=Casari%2C+Paolo&rft.date=2024-02-01&rft.issn=1530-437X&rft.eissn=1558-1748&rft.volume=24&rft.issue=3&rft.spage=3157&rft.epage=3171&rft_id=info:doi/10.1109%2FJSEN.2023.3339369&rft.externalDBID=n%2Fa&rft.externalDocID=10_1109_JSEN_2023_3339369
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1530-437X&client=summon
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1530-437X&client=summon
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1530-437X&client=summon