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The paper presents two methods of updating the weights of a Gaussian mixture to account for the density propagation within a data assimilation setting. The evolution of the first two moments of the Gaussian components is given by the linearized model of the system. When observations are available, both the moments and the weights are updated to obtain a better approximation to the a posteriori probability...
Linear filtering in the presence of timing uncertainty is considered. In the model assumed here the true measurement times are intermittently available and noisy measurement times are always available. The estimation problem involves jointly estimating the state and the timing error parameters. The optimal Bayesian estimator cannot be found in closed-form so three approximations are proposed. The...
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