Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Hyun, Eugin | - |
dc.contributor.author | Jin, YoungSeok | - |
dc.date.accessioned | 2020-07-07T10:42:13Z | - |
dc.date.available | 2020-07-07T10:42:13Z | - |
dc.date.created | 2020-04-23 | - |
dc.date.issued | 2020-04 | - |
dc.identifier.citation | Sensors, v.20, no.7 | - |
dc.identifier.issn | 1424-8220 | - |
dc.identifier.uri | http://hdl.handle.net/20.500.11750/12044 | - |
dc.description.abstract | In this paper, we propose a Doppler-spectrum feature-based human–vehicle classification scheme for an FMCW (frequency-modulated continuous wave) radar sensor. We introduce three novel features referred to as the scattering point count, scattering point difference, and magnitude difference rate features based on the characteristics of the Doppler spectrum in two successive frames. We also use an SVM (support vector machine) and BDT (binary decision tree) for training and validation of the three aforementioned features. We measured the signals using a 24-GHz FMCW radar front-end module and a real-time data acquisition module and extracted three features from a walking human and a moving vehicle in the field. We then repeatedly measured the classification decision rate of the proposed algorithm using the SVM and BDT, finding that the average performance exceeded 99% and 96% for the walking human and the moving vehicle, respectively. © 2020 by the authors. Licensee MDPI, Basel, Switzerland. | - |
dc.language | English | - |
dc.publisher | MDPI AG | - |
dc.title | Doppler-Spectrum Feature-Based Human-Vehicle Classification Scheme Using Machine Learning for an FMCW Radar Sensor | - |
dc.type | Article | - |
dc.identifier.doi | 10.3390/s20072001 | - |
dc.identifier.wosid | 000537110500197 | - |
dc.identifier.scopusid | 2-s2.0-85083071780 | - |
dc.type.local | Article(Overseas) | - |
dc.type.rims | ART | - |
dc.description.journalClass | 1 | - |
dc.citation.publicationname | Sensors | - |
dc.identifier.citationVolume | 20 | - |
dc.identifier.citationNumber | 7 | - |
dc.identifier.citationTitle | Sensors | - |
dc.type.journalArticle | Article | - |
dc.description.isOpenAccess | Y | - |
dc.subject.keywordAuthor | human detection | - |
dc.subject.keywordAuthor | FMCW radar | - |
dc.subject.keywordAuthor | range-Doppler processing | - |
dc.subject.keywordAuthor | radar machine learning | - |
dc.subject.keywordPlus | Classification decision | - |
dc.subject.keywordPlus | FMCW radar sensors | - |
dc.subject.keywordPlus | Frequency-modulated continuous waves | - |
dc.subject.keywordPlus | Front end modules | - |
dc.subject.keywordPlus | Real time data acquisition | - |
dc.subject.keywordPlus | SVM(support vector machine) | - |
dc.subject.keywordPlus | Vehicle classification | - |
dc.subject.keywordPlus | Radar measurement | - |
dc.subject.keywordPlus | Binary trees | - |
dc.subject.keywordPlus | Continuous wave radar | - |
dc.subject.keywordPlus | Data acquisition | - |
dc.subject.keywordPlus | Decision trees | - |
dc.subject.keywordPlus | Doppler effect | - |
dc.subject.keywordPlus | Frequency modulation | - |
dc.subject.keywordPlus | Radar equipment | - |
dc.subject.keywordPlus | Spectrum analysis | - |
dc.subject.keywordPlus | Support vector machines | - |
dc.subject.keywordPlus | Vehicles | - |
dc.subject.keywordPlus | Binary decision trees | - |
dc.contributor.affiliatedAuthor | Hyun, Eugin | - |
dc.contributor.affiliatedAuthor | Jin, YoungSeok | - |