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AuthorSchlichenmaier, Johannesdc.contributor.author
AuthorRoos, Fabiandc.contributor.author
AuthorHügler, Philippdc.contributor.author
AuthorWaldschmidt, Christiandc.contributor.author
Date of accession2019-07-17T06:40:27Zdc.date.accessioned
Available in OPARU since2019-07-17T06:40:27Zdc.date.available
Date of first publication2019-06-03dc.date.issued
AbstractAs high resolution automotive radars become more common, so does their usage for next-generation functionalities like advanced driver assistant systems and autonomous driving. This creates the need for robust clustering techniques to distinguish among multiple extended objects like vehicles in the same scenario. One especially challenging scenario is that of separating two extended targets close to each other, each following its own trajectory. This paper proposes a clustering algorithm based on the analysis of the velocity profile to divide target points of multiple vehicles into sub-clusters. The theoretical background is explained and shown on simulation data. The algorithm is verified using radar measurements of two extended vehicular targets.dc.description.abstract
Languageen_USdc.language.iso
PublisherUniversität Ulmdc.publisher
LicenseStandarddc.rights
Link to license texthttps://oparu.uni-ulm.de/xmlui/license_v3dc.rights.uri
KeywordAutomotive Radar, Radar Signal Processing, Clusteringdc.subject
Dewey Decimal GroupDDC 620 / Engineering & allied operationsdc.subject.ddc
LCSHRadar in navigationdc.subject.lcsh
LCSHCluster analysisdc.subject.lcsh
LCSHRadardc.subject.lcsh
LCSHSignal processingdc.subject.lcsh
LCSHWheelsdc.subject.lcsh
LCSHAutonomous vehiclesdc.subject.lcsh
LCSHClustering; Algorithmsdc.subject.lcsh
LCSHDriver assistance systemsdc.subject.lcsh
TitleClustering of closely adjacent extended objects in radar images using velocity profile analysisdc.title
Resource typeBeitrag zu einer Konferenzdc.type
VersionacceptedVersiondc.description.version
DOIhttp://dx.doi.org/10.18725/OPARU-16383dc.identifier.doi
URNhttp://nbn-resolving.de/urn:nbn:de:bsz:289-oparu-16440-2dc.identifier.urn
GNDBordradardc.subject.gnd
GNDCluster-Analysedc.subject.gnd
GNDRadardc.subject.gnd
GNDSignalverarbeitungdc.subject.gnd
GNDGeschwindigkeitsverteilungdc.subject.gnd
GNDAutonomes Fahrzeugdc.subject.gnd
GNDReifendc.subject.gnd
GNDSensordc.subject.gnd
FacultyFakultät für Ingenieurwissenschaften, Informatik und Psychologieuulm.affiliationGeneral
InstitutionInstitut für Mikrowellentechnikuulm.affiliationSpecific
Peer reviewjauulm.peerReview
DCMI TypeTextuulm.typeDCMI
CategoryPublikationenuulm.category
DOI of original publication10.1109/ICMIM.2019.8726765dc.relation1.doi
Source - Title of source2019 IEEE MTT-S International Conference on Microwaves for Intelligent Mobility (ICMIM)source.title
Source - Place of publicationInstitute of Electrical and Electronics Engineerssource.publisher
Source - Volume2019source.volume
Source - Year2019source.year
Source - From page62source.fromPage
Source - To page65source.toPage
Source - ISBN978-1-7281-0775-2source.identifier.isbn
Source - ISBN978-1-7281-0776-9source.identifier.isbn
FundingKoRRund / BMBF [16ES0580]uulm.funding
Conference name2019 International Conference on Microwaves for Intelligent Mobility (ICMIM)uulm.conferenceName
Conference placeDetroituulm.conferencePlace
Conference start date2019-04-15uulm.conferenceStartDate
Conference end date2019-04-16uulm.conferenceEndDate
Bibliographyuulmuulm.bibliographie


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