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Unbiased minimum-variance linear state estimation. (English) Zbl 0627.93065
A method is developed for linear estimation in the presence of unknown or highly non-Gaussian system inputs. The state update is determined so that it is unaffected by the unknown inputs. The filter may not be globally optimum in the mean square error sense. However, it performs well when the unknown inputs take extreme or unexpected values. In many geophysical and environmental applications, it is performance during these periods which counts the most. The application of the filter is illustrated in the real-time estimation of mean areal precipitation.

93E10 Estimation and detection in stochastic control theory
93C05 Linear systems in control theory
93E11 Filtering in stochastic control theory
62M20 Inference from stochastic processes and prediction
86A10 Meteorology and atmospheric physics
93C95 Application models in control theory
Full Text: DOI
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