State Estimation in the Presence of non-Gaussian Noise
نویسنده
چکیده
The problem of nonlinear filtering with a non-Gaussian model of measurement errors is considered in this paper: Based on Bayes classification of the observations an approximate solution is introduced. The Bayesian estimator can be applied to any discrete time, lineal; or nonlinear system which is observed in additive non-Gaussian measurement noise. The problem of narrowband inte$erence suppression in additive noise is considered as an important example of non-Gaussian noisejltering. It is shown that the approximate filter outperforms currently used approaches and at the same time offers simplicity in the design.
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تاریخ انتشار 2000