DC Field | Value | Language |
---|---|---|
dc.contributor.author | Youn, Wonkeun | ko |
dc.contributor.author | Huang, Yulong | ko |
dc.contributor.author | Myung, Hyun | ko |
dc.date.accessioned | 2020-06-18T05:20:04Z | - |
dc.date.available | 2020-06-18T05:20:04Z | - |
dc.date.created | 2019-11-22 | - |
dc.date.created | 2019-11-22 | - |
dc.date.issued | 2020-07 | - |
dc.identifier.citation | IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, v.69, no.7, pp.5166 - 5182 | - |
dc.identifier.issn | 0018-9456 | - |
dc.identifier.uri | http://hdl.handle.net/10203/274711 | - |
dc.description.abstract | This article proposes a new skewed outlier-robust localization algorithm that is based on time-difference of arrival (TDOA) measurements at an airport. A new outlier-robust filtering framework is derived based on the skew Gaussian-gamma mixture (SGGM) distribution, where the state, a mixing parameter, a shape parameter, a scale matrix, and the degrees of freedom (DOFs) are inferred simultaneously using variational Bayesian (VB) approach. An interacting multiple-model (IMM) filter with different kinematic system models is implemented to handle the multimodal dynamics of the vehicle, yielding the IMM-SGGM algorithm. In particular, a new measurement likelihood based on the SGGM distribution is derived utilizing VB inference for the combination procedure in the proposed IMM-SGGM algorithm. Car-mounted experiments using TDOA measurements at an airport were conducted to verify the effectiveness of the proposed algorithm. The performance of the proposed IMM-SGGM algorithm is evaluated through comparisons with the state-of-the-art approaches. The experimental results demonstrate that the proposed IMM-SGGM algorithm has better localization accuracy and robustness to skewed outlier measurements than the state-of-the-art approaches. | - |
dc.language | English | - |
dc.publisher | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC | - |
dc.title | Robust Localization Using IMM Filter Based on Skew Gaussian-Gamma Mixture Distribution in Mixed LOS/NLOS Condition | - |
dc.type | Article | - |
dc.identifier.wosid | 000542954500055 | - |
dc.identifier.scopusid | 2-s2.0-85086715774 | - |
dc.type.rims | ART | - |
dc.citation.volume | 69 | - |
dc.citation.issue | 7 | - |
dc.citation.beginningpage | 5166 | - |
dc.citation.endingpage | 5182 | - |
dc.citation.publicationname | IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT | - |
dc.identifier.doi | 10.1109/TIM.2019.2955536 | - |
dc.contributor.localauthor | Myung, Hyun | - |
dc.contributor.nonIdAuthor | Huang, Yulong | - |
dc.description.isOpenAccess | N | - |
dc.type.journalArticle | Article | - |
dc.subject.keywordAuthor | Noise measurement | - |
dc.subject.keywordAuthor | Inference algorithms | - |
dc.subject.keywordAuthor | Shape | - |
dc.subject.keywordAuthor | Time measurement | - |
dc.subject.keywordAuthor | Kalman filters | - |
dc.subject.keywordAuthor | Atmospheric measurements | - |
dc.subject.keywordAuthor | Particle measurements | - |
dc.subject.keywordAuthor | Interacting multiple model (IMM) | - |
dc.subject.keywordAuthor | localization | - |
dc.subject.keywordAuthor | outlier | - |
dc.subject.keywordAuthor | skew Gaussian-gamma mixture (SGGM) | - |
dc.subject.keywordPlus | INTERACTING MULTIPLE MODEL | - |
dc.subject.keywordPlus | KALMAN | - |
dc.subject.keywordPlus | TRACKING | - |
dc.subject.keywordPlus | NETWORKS | - |
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