DC Field | Value | Language |
---|---|---|
dc.contributor.author | Youn, Wonkeun | ko |
dc.contributor.author | Ko, Nak Yong | ko |
dc.contributor.author | Gadsden, Stephen | ko |
dc.contributor.author | Myung, Hyun | ko |
dc.date.accessioned | 2021-01-14T03:10:04Z | - |
dc.date.available | 2021-01-14T03:10:04Z | - |
dc.date.created | 2020-09-17 | - |
dc.date.created | 2020-09-17 | - |
dc.date.issued | 2021-01 | - |
dc.identifier.citation | IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, v.70 | - |
dc.identifier.issn | 0018-9456 | - |
dc.identifier.uri | http://hdl.handle.net/10203/279912 | - |
dc.description.abstract | This article proposes a novel adaptive Kalman filter (AKF) to estimate the unknown probability of measurement loss using the interacting multiple-model (IMM) filtering framework, yielding the IMM-AKF algorithm. In the proposed IMM-AKF algorithm, the state, Bernoulli random variable, and measurement loss probability are jointly inferred based on the variational Bayesian (VB) approach. In particular, a new likelihood definition is derived for the mode probability update process of the IMM-AKF algorithm. Experiments demonstrate the superiority of the proposed IMM-AKF algorithm over existing filtering algorithms by adaptively estimating the unknown time-varying measurement loss probability. | - |
dc.language | English | - |
dc.publisher | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC | - |
dc.title | A Novel Multiple-Model Adaptive Kalman Filter for an Unknown Measurement Loss Probability | - |
dc.type | Article | - |
dc.identifier.wosid | 000597200000041 | - |
dc.identifier.scopusid | 2-s2.0-85097731468 | - |
dc.type.rims | ART | - |
dc.citation.volume | 70 | - |
dc.citation.publicationname | IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT | - |
dc.identifier.doi | 10.1109/TIM.2020.3023213 | - |
dc.contributor.localauthor | Myung, Hyun | - |
dc.contributor.nonIdAuthor | Ko, Nak Yong | - |
dc.contributor.nonIdAuthor | Gadsden, Stephen | - |
dc.description.isOpenAccess | N | - |
dc.type.journalArticle | Article | - |
dc.subject.keywordAuthor | Interacting multiple model | - |
dc.subject.keywordAuthor | Kalman filter (KF) | - |
dc.subject.keywordAuthor | localization | - |
dc.subject.keywordAuthor | measurement loss | - |
dc.subject.keywordAuthor | variational Bayesian (VB) inference | - |
dc.subject.keywordPlus | SENSOR | - |
dc.subject.keywordPlus | TRACKING | - |
dc.subject.keywordPlus | NETWORK | - |
dc.subject.keywordPlus | GPS | - |
dc.subject.keywordPlus | LOCALIZATION | - |
dc.subject.keywordPlus | FUSION | - |
dc.subject.keywordPlus | INS | - |
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