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dc.contributor.author Kim, Sangdong -
dc.contributor.author Kim, Bong-Seok -
dc.contributor.author Ju, Yeonghwan -
dc.contributor.author Lee, Jonghun -
dc.date.available 2018-01-25T01:06:29Z -
dc.date.created 2017-09-11 -
dc.date.issued 2017 -
dc.identifier.issn 1392-1215 -
dc.identifier.uri http://hdl.handle.net/20.500.11750/5030 -
dc.description.abstract This paper proposes a low-complexity spectral partitioning (SP) based MUSIC algorithm for automotive radar. For short-range radar (SRR), the range accuracy and resolution of 24 GHz ISM band radar should be improved because the requirements of automotive sensing become more demanding over time. To improve the performance of range estimation, high resolution based algorithms such as the estimation of signal parameters via rotational invariance techniques (ESPRIT) and multiple signal classification (MUSIC) have been proposed. However, in a low signal-tonoise ratio (SNR), the high resolution algorithm shows degraded performance to estimate the parameters. To solve this problem, SP based high resolution algorithms have been studied recently. However, for real-time operation, the conventional SP method cannot be applied to automotive radar due to its high complexity. Therefore, a low complexity SP based MUSIC is designed to maintain the performance of the range accuracy and resolution in a low SNR environment. While the complexity of the proposed algorithm is less than the SP-MUSIC, Monte-Carlo simulation results and experimental results show that the estimation performance of the proposed method is similar to that of SP-MUSIC in terms of various parameters. -
dc.language English -
dc.publisher Kauno Technologijos Universitetas -
dc.title Low-complexity spectral partitioning based MUSIC algorithm for automotive radar -
dc.type Article -
dc.identifier.doi 10.5755/j01.eie.23.4.18719 -
dc.identifier.wosid 000407181800006 -
dc.identifier.scopusid 2-s2.0-85027162886 -
dc.identifier.bibliographicCitation Elektronika ir Elektrotechnika, v.23, no.4, pp.33 - 38 -
dc.description.isOpenAccess FALSE -
dc.subject.keywordAuthor Vehicle radar -
dc.subject.keywordAuthor spectrum partitioning -
dc.subject.keywordAuthor MUSIC -
dc.subject.keywordAuthor low SNR -
dc.subject.keywordAuthor low complexity -
dc.citation.endPage 38 -
dc.citation.number 4 -
dc.citation.startPage 33 -
dc.citation.title Elektronika ir Elektrotechnika -
dc.citation.volume 23 -
dc.description.journalRegisteredClass scie -
dc.description.journalRegisteredClass scopus -
dc.relation.journalResearchArea Engineering -
dc.relation.journalWebOfScienceCategory Engineering, Electrical & Electronic -
dc.type.docType Article -
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Appears in Collections:
Division of Automotive Technology Advanced Radar Tech. Lab 1. Journal Articles
Division of Automotive Technology 1. Journal Articles

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