A new IMM interacting approach for unequal dimension states for multitarget tracking in cluttered environments
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Park, Seung Hyo | - |
dc.contributor.author | Song, Taek Lyul | - |
dc.contributor.author | Oh, Raegeun | - |
dc.contributor.author | Choi, Jee Woong | - |
dc.date.accessioned | 2022-10-07T09:18:57Z | - |
dc.date.available | 2022-10-07T09:18:57Z | - |
dc.date.issued | 2021-12 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/110432 | - |
dc.description.abstract | Since it is unknown in advance whether the target is maneuvering in practical target tracking environments, multiple model tracking techniques are introduced by applying various target dynamic models. Among the multiple model tracking techniques, interacting multiple model (IMM) method has shown excellent performance with low complexity due to the interaction process of each state of mode. When various dynamic models are designed, the dimension of each state may be unequal, which may cause biased estimate. To deal with this problem, mode interacting approaches to two dynamic models of unequal dimensions have been studied in other literatures. Here, a new interacting approach for the case of three dynamic models with unequal dimensions is proposed to reduce the bias in the extra state estimates of the higher dimensional modes, and it is shown that the tracking performance is better than the existing IMM algorithm with the conventional interaction step through Monte Carlo simulation for multi-target tracking in cluttered environments. | - |
dc.format.extent | 6 | - |
dc.language | 영어 | - |
dc.language.iso | ENG | - |
dc.publisher | IEEE | - |
dc.title | A new IMM interacting approach for unequal dimension states for multitarget tracking in cluttered environments | - |
dc.type | Article | - |
dc.publisher.location | 미국 | - |
dc.identifier.doi | 10.1109/ICCAIS52680.2021.9624630 | - |
dc.identifier.scopusid | 2-s2.0-85123983756 | - |
dc.identifier.bibliographicCitation | 10th International Conference on Control, Automation and Information Sciences, ICCAIS 2021 - Proceedings, pp 28 - 33 | - |
dc.citation.title | 10th International Conference on Control, Automation and Information Sciences, ICCAIS 2021 - Proceedings | - |
dc.citation.startPage | 28 | - |
dc.citation.endPage | 33 | - |
dc.type.docType | Conference Paper | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | scopus | - |
dc.subject.keywordPlus | Clutter (information theory) | - |
dc.subject.keywordPlus | Intelligent systems | - |
dc.subject.keywordPlus | Monte Carlo methods | - |
dc.subject.keywordPlus | Target tracking | - |
dc.subject.keywordPlus | Cluttered environments | - |
dc.subject.keywordPlus | Dynamics models | - |
dc.subject.keywordPlus | Interacting approach | - |
dc.subject.keywordPlus | Interacting multiple model | - |
dc.subject.keywordPlus | Multi-target-tracking | - |
dc.subject.keywordPlus | Multiple model tracking | - |
dc.subject.keywordPlus | Multitarget tracking cluttered environment | - |
dc.subject.keywordPlus | Targets tracking | - |
dc.subject.keywordPlus | Tracking techniques | - |
dc.subject.keywordPlus | Unequal dimension | - |
dc.subject.keywordPlus | Dynamic models | - |
dc.subject.keywordAuthor | Interacting approach | - |
dc.subject.keywordAuthor | Interacting Multiple Model | - |
dc.subject.keywordAuthor | Multitarget tracking cluttered environments | - |
dc.subject.keywordAuthor | Unequal dimensions | - |
dc.identifier.url | https://ieeexplore.ieee.org/document/9624630/ | - |
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