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Non-Supervised High Resolution Doppler Machine Learning for Pathological Radar Clutter

hal.structure.identifierInstitut de Mathématiques de Bordeaux [IMB]
hal.structure.identifierThales LAS France
dc.contributor.authorCABANES, Yann
hal.structure.identifierThales Air Systems
dc.contributor.authorBARBARESCO, Frédéric
hal.structure.identifierInstitut de Mathématiques de Bordeaux [IMB]
dc.contributor.authorARNAUDON, Marc
hal.structure.identifierInstitut de Mathématiques de Bordeaux [IMB]
dc.contributor.authorBIGOT, Jérémie
dc.date.accessioned2024-04-04T02:52:06Z
dc.date.available2024-04-04T02:52:06Z
dc.date.conference2020-09-23
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/192031
dc.description.abstractEnIn this paper we propose a method to classify radar clutter from radar data using a non-supervised classification algorithm. As a final objective, new radars will therefore be able to use the experience of other radars to improve their performances: learning pathological radar clutter can be used to fix some false alarm rate created by strong echoes coming from hail, rain, waves, mountains, cities; it will also improve the detectability of slow moving targets, like drones, which can be hidden in the clutter, flying close to the landform.
dc.language.isoen
dc.source.title2019 International Radar Conference (RADAR)
dc.subject.ennon-supervised classification
dc.subject.enmachine learning
dc.subject.enradar clutter
dc.subject.enk-means
dc.subject.enautocorrelation matrix
dc.subject.enBurg algorithm
dc.subject.enreflection coefficients
dc.subject.enKähler metric
dc.title.enNon-Supervised High Resolution Doppler Machine Learning for Pathological Radar Clutter
dc.typeCommunication dans un congrès
dc.identifier.doi10.1109/RADAR41533.2019.171295
dc.subject.halMathématiques [math]
dc.subject.halMathématiques [math]/Géométrie métrique [math.MG]
dc.subject.halMathématiques [math]/Géométrie différentielle [math.DG]
dc.subject.halStatistiques [stat]/Machine Learning [stat.ML]
dc.subject.halInformatique [cs]/Intelligence artificielle [cs.AI]
dc.subject.halStatistiques [stat]
dc.subject.halInformatique [cs]
dc.subject.halInformatique [cs]/Traitement du signal et de l'image
dc.subject.halPhysique [physics]
bordeaux.hal.laboratoriesInstitut de Mathématiques de Bordeaux (IMB) - UMR 5251*
bordeaux.institutionUniversité de Bordeaux
bordeaux.institutionBordeaux INP
bordeaux.institutionCNRS
bordeaux.conference.titleRADAR 2019
bordeaux.countryFR
bordeaux.title.proceeding2019 International Radar Conference (RADAR)
bordeaux.conference.cityToulon
bordeaux.peerReviewedoui
hal.identifierhal-02875415
hal.version1
hal.invitednon
hal.proceedingsoui
hal.popularnon
hal.audienceInternationale
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-02875415v1
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.btitle=2019%20International%20Radar%20Conference%20(RADAR)&rft.au=CABANES,%20Yann&BARBARESCO,%20Fr%C3%A9d%C3%A9ric&ARNAUDON,%20Marc&BIGOT,%20J%C3%A9r%C3%A9mie&rft.genre=unknown


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