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Cooperative mmWave PHD-SLAM with Moving Scatterers
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Kim, Hyowon | - |
| dc.contributor.author | Lee, Jaebok | - |
| dc.contributor.author | Ge, Yu | - |
| dc.contributor.author | Jiang, Fan | - |
| dc.contributor.author | Kim, Sunwoo | - |
| dc.contributor.author | Wymeersch, Henk | - |
| dc.date.accessioned | 2022-09-19T12:17:56Z | - |
| dc.date.available | 2022-09-19T12:17:56Z | - |
| dc.date.created | 2022-09-08 | - |
| dc.date.issued | 2022-07 | - |
| dc.identifier.issn | 0000-0000 | - |
| dc.identifier.uri | https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/171555 | - |
| dc.description.abstract | Simultaneous localization and mapping (SLAM) using multipath at mmWave frequencies can provide accurate localization in the presence of static landmarks. When radio signals reflected from moving vehicle scatterers (VSs) are observed, the standard SLAM filters exhibit a degraded performance. To address this problem, we propose a probability hypothesis density (PHD)-based SLAM filter, where separate maps are maintained for VS and other types of landmarks. Through a combination of developed (i) local PHD-SLAM and (ii) global map fusion, we demonstrate that the proposed filter can handle the problem. | - |
| dc.language | 영어 | - |
| dc.language.iso | en | - |
| dc.publisher | Institute of Electrical and Electronics Engineers Inc. | - |
| dc.title | Cooperative mmWave PHD-SLAM with Moving Scatterers | - |
| dc.type | Article | - |
| dc.contributor.affiliatedAuthor | Kim, Sunwoo | - |
| dc.identifier.doi | 10.23919/FUSION49751.2022.9841389 | - |
| dc.identifier.scopusid | 2-s2.0-85136571233 | - |
| dc.identifier.wosid | 000855689000159 | - |
| dc.identifier.bibliographicCitation | 2022 25th International Conference on Information Fusion, FUSION 2022, pp.1 - 6 | - |
| dc.relation.isPartOf | 2022 25th International Conference on Information Fusion, FUSION 2022 | - |
| dc.citation.title | 2022 25th International Conference on Information Fusion, FUSION 2022 | - |
| dc.citation.startPage | 1 | - |
| dc.citation.endPage | 6 | - |
| dc.type.rims | ART | - |
| dc.type.docType | Conference Paper | - |
| dc.description.journalClass | 1 | - |
| dc.description.isOpenAccess | N | - |
| dc.description.journalRegisteredClass | scie | - |
| dc.description.journalRegisteredClass | scopus | - |
| dc.relation.journalResearchArea | Computer Science | - |
| dc.relation.journalWebOfScienceCategory | Computer Science, Artificial Intelligence | - |
| dc.relation.journalWebOfScienceCategory | Computer Science, Theory & Methods | - |
| dc.subject.keywordPlus | Information fusion | - |
| dc.subject.keywordPlus | Robotics | - |
| dc.subject.keywordPlus | Millimeter waves | - |
| dc.subject.keywordPlus | Degraded performance | - |
| dc.subject.keywordPlus | Density-based | - |
| dc.subject.keywordPlus | Localisation | - |
| dc.subject.keywordPlus | Mm waves | - |
| dc.subject.keywordPlus | Mm-wave frequencies | - |
| dc.subject.keywordPlus | Moving vehicles | - |
| dc.subject.keywordPlus | Multipath | - |
| dc.subject.keywordPlus | Probability hypothesis density | - |
| dc.subject.keywordPlus | Radio signals | - |
| dc.subject.keywordPlus | Simultaneous localization and mapping | - |
| dc.subject.keywordAuthor | ALGORITHMS | - |
| dc.subject.keywordAuthor | TRACKING | - |
| dc.subject.keywordAuthor | FILTER | - |
| dc.identifier.url | https://ieeexplore.ieee.org/document/9841389 | - |
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