Joint CKF-PHD Filter and Map Fusion for 5G Multi-cell SLAM
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kim, Hyowon | - |
dc.contributor.author | Granstrom, Karl | - |
dc.contributor.author | Gao, Lin | - |
dc.contributor.author | Battistelli, Giorgio | - |
dc.contributor.author | Kim, Sunwoo | - |
dc.contributor.author | Wymeersch, Henk | - |
dc.date.accessioned | 2021-08-02T09:27:18Z | - |
dc.date.available | 2021-08-02T09:27:18Z | - |
dc.date.created | 2021-05-11 | - |
dc.date.issued | 2020-06 | - |
dc.identifier.issn | 1550-3607 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/9784 | - |
dc.description.abstract | 5G is expected to enable simultaneous vehicle localization and environment mapping (SLAM). Furthermore, vehicular networks will be covered with 5G small cells, wherein the map information is collected at each base station (BS) and then fused so as to promote the overall performance of SLAM. In 5G multi-cell SLAM, there are challenges such as the unknown number of targets, uncertainty regarding the association between the targets and the measurements, unknown types of targets, as well as map management among BSs. To address those challenges, we propose a new method for 5G multi-cell SLAM which comprises a joint cubature Kalman filter and multi-model probability hypothesis density, and a map fusion routine. Simulation results demonstrate that the proposed method solves the aforementioned challenges and also improves vehicle state and map estimates. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | Institute of Electrical and Electronics Engineers Inc. | - |
dc.title | Joint CKF-PHD Filter and Map Fusion for 5G Multi-cell SLAM | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Kim, Sunwoo | - |
dc.identifier.doi | 10.1109/ICC40277.2020.9149211 | - |
dc.identifier.scopusid | 2-s2.0-85089433923 | - |
dc.identifier.bibliographicCitation | IEEE International Conference on Communications, v.2020-June, pp.1 - 6 | - |
dc.relation.isPartOf | IEEE International Conference on Communications | - |
dc.citation.title | IEEE International Conference on Communications | - |
dc.citation.volume | 2020-June | - |
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 | scopus | - |
dc.subject.keywordPlus | Cells | - |
dc.subject.keywordPlus | Cytology | - |
dc.subject.keywordPlus | Kalman filters | - |
dc.subject.keywordPlus | Uncertainty analysis | - |
dc.subject.keywordPlus | Cubature kalman filters | - |
dc.subject.keywordPlus | Environment mapping | - |
dc.subject.keywordPlus | Map managements | - |
dc.subject.keywordPlus | PHD filters | - |
dc.subject.keywordPlus | Small cells | - |
dc.subject.keywordPlus | Vehicle localization | - |
dc.subject.keywordPlus | Vehicle state | - |
dc.subject.keywordPlus | Vehicular networks | - |
dc.subject.keywordPlus | 5G mobile communication systems | - |
dc.subject.keywordAuthor | 5G multi-cell SLAM | - |
dc.subject.keywordAuthor | joint CKF | - |
dc.subject.keywordAuthor | map fusion | - |
dc.subject.keywordAuthor | message passing | - |
dc.subject.keywordAuthor | PHD | - |
dc.identifier.url | https://ieeexplore.ieee.org/document/9149211 | - |
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