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.
Uncertain Timestamps in Linear State Estimation
IEEE Transactions on Aerospace and Electronic Systems ; 55 , 3 ; 1334-1346
2019-06-01
2203197 byte
Article (Journal)
Electronic Resource
English
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