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dc.contributor.author Hyun, Eugin ko
dc.contributor.author Jin, Young-Seok ko
dc.contributor.author Park, Jae-Hyun ko
dc.contributor.author Yang, Jong-Ryul ko
dc.date.accessioned 2021-01-22T07:24:17Z -
dc.date.available 2021-01-22T07:24:17Z -
dc.date.created 2020-11-13 -
dc.date.issued 2020-11 -
dc.identifier.citation Sensors, v.20, no.21, pp.1 - 20 -
dc.identifier.issn 1424-8220 -
dc.identifier.uri http://hdl.handle.net/20.500.11750/12756 -
dc.description.abstract In this paper, we propose a Doppler spectrum-based passenger detection scheme for a CW (Continuous Wave) radar sensor in vehicle applications. First, we design two new features, referred to as an ‘extended degree of scattering points’ and a ‘different degree of scattering points’ to represent the characteristics of the non-rigid motion of a moving human in a vehicle. We also design one newly defined feature referred to as the ‘presence of vital signs’, which is related to extracting the Doppler frequency of chest movements due to breathing. Additionally, we use a BDT (Binary Decision Tree) for machine learning during the training and test steps with these three extracted features. We used a 2.45 GHz CW radar front-end module with a single receive antenna and a real-time data acquisition module. Moreover, we built a test-bed with a structure similar to that of an actual vehicle interior. With the test-bed, we measured radar signals in various scenarios. We then repeatedly assessed the classification accuracy and classification error rate using the proposed algorithm with the BDT. We found an average classification accuracy rate of 98.6% for a human with or without motion. © 2020 by the authors. Licensee MDPI, Basel, Switzerland. -
dc.language English -
dc.publisher Multidisciplinary Digital Publishing Institute (MDPI) -
dc.title Machine Learning-Based Human Recognition Scheme Using a Doppler Radar Sensor for In-Vehicle Applications -
dc.type Article -
dc.identifier.doi 10.3390/s20216202 -
dc.identifier.wosid 000589420100001 -
dc.identifier.scopusid 2-s2.0-85094603226 -
dc.type.local Article(Overseas) -
dc.type.rims ART -
dc.description.journalClass 1 -
dc.contributor.localauthor Hyun, Eugin -
dc.contributor.localauthor Jin, Young-Seok -
dc.contributor.nonIdAuthor Park, Jae-Hyun -
dc.contributor.nonIdAuthor Yang, Jong-Ryul -
dc.identifier.citationVolume 20 -
dc.identifier.citationNumber 21 -
dc.identifier.citationStartPage 1 -
dc.identifier.citationEndPage 20 -
dc.identifier.citationTitle Sensors -
dc.type.journalArticle Article -
dc.description.isOpenAccess Y -
dc.subject.keywordAuthor passenger detection -
dc.subject.keywordAuthor CW radar -
dc.subject.keywordAuthor radar feature vector -
dc.subject.keywordAuthor radar machine learning -

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