Abstract
A nonlinear estimation problem often encountered in processing navigation data is considered. The linear optimal estimator (LOE) that minimizes the root mean-square (RMS) criterion in the class of linear estimates for this nonlinear estimation problem is investigated. The equivalent linear models for nonlinear measurements have been introduced for the LOE and the Cramer-Rao Bound. The features of the LOE in comparison with the Bayesian nonlinear optimal estimator (NOE), which corresponds to the conditional mean, are studied. Some examples are considered to illustrate the results obtained.
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