Abstract
The problem of estimating parameters of random sequences used to describe sensor errors is formulated and solved in the context of the Bayesian approach as a nonlinear filtering problem. The algorithms that provide the possibility of obtaining optimal estimates and calculation of potential estimation accuracy have been designed. The possibility of calculating the Cramer-Rao Lower Bound is discussed. Two examples are given to illustrate the application of the proposed approach.
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