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dc.contributor.authorChiang, Cheng-Tseen_US
dc.contributor.authorTseng, Po-Hsuanen_US
dc.contributor.authorFeng, Kai-Tenen_US
dc.date.accessioned2014-12-08T15:22:04Z-
dc.date.available2014-12-08T15:22:04Z-
dc.date.issued2012-02-01en_US
dc.identifier.issn0018-9545en_US
dc.identifier.urihttp://dx.doi.org/10.1109/TVT.2011.2180939en_US
dc.identifier.urihttp://hdl.handle.net/11536/15670-
dc.description.abstractLocation estimation and tracking for mobile stations have attracted a significant amount of attention in recent years. Different types of signal sources are considered available to provide measurement inputs for location estimation and tracking in heterogeneous wireless networks. Various techniques have been studied and combined for location tracking, e. g., the least square methods for location estimation associated with the Kalman filters for location tracking. In this paper, the hybrid unified Kalman tracking (HUKT) technique is proposed to provide an integrated algorithm for precise location tracking based on both time of arrival (TOA) and time difference of arrival (TDOA) measurements. A new variable is incorporated as an additional state within the Kalman filtering formulation to consider the nonlinear behavior in the measurement update process. The relationship between this new variable and the desired location estimate is applied in the state update process of the Kalman filter. Three different designs of hybrid factor are proposed to adaptively adjust the weighting value between the TOA and TDOA measurements. Moreover, similar concepts are also utilized in the design of unified Kalman tracking schemes for pure TOA and TDOA measurement inputs in this paper. Compared with existing schemes, numerical results illustrate that the proposed HUKT algorithm can achieve enhanced accuracy for mobile location tracking, particularly under environments with an insufficient number of measurements in one of the signal paths.en_US
dc.language.isoen_USen_US
dc.subjectKalman filteren_US
dc.subjectmobile location estimation and trackingen_US
dc.subjecttime difference of arrival (TDOA)en_US
dc.subjecttime of arrival (TOA)en_US
dc.titleHybrid Unified Kalman Tracking Algorithms for Heterogeneous Wireless Location Systemsen_US
dc.typeArticleen_US
dc.identifier.doi10.1109/TVT.2011.2180939en_US
dc.identifier.journalIEEE TRANSACTIONS ON VEHICULAR TECHNOLOGYen_US
dc.citation.volume61en_US
dc.citation.issue2en_US
dc.citation.spage702en_US
dc.citation.epage715en_US
dc.contributor.department電子物理學系zh_TW
dc.contributor.departmentDepartment of Electrophysicsen_US
dc.identifier.wosnumberWOS:000300427400024-
dc.citation.woscount1-
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