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• W2891376912 abstract "We consider a linear state estimation problem, where, in addition to the usual timestamped measurements, observations with uncertain timestamps are available. Such observations could, e.g., come from traces left by a target in a tracking scenario or from witnesses of an event and have the potential to improve the estimation accuracy significantly. We derive the posterior distribution and point estimators for a linear Gaussian smoothing formulation of this problem and illustrate with two numerical examples." @default.
• W2891376912 created "2018-09-27" @default.
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• W2891376912 date "2019-06-01" @default.
• W2891376912 modified "2023-09-27" @default.
• W2891376912 title "Uncertain Timestamps in Linear State Estimation" @default.
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• W2891376912 doi "https://doi.org/10.1109/taes.2018.2869648" @default.
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