کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
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4630983 | 1340613 | 2011 | 12 صفحه PDF | دانلود رایگان |
![عکس صفحه اول مقاله: Nonlinear estimation applying an unscented transformation in systems with correlated uncertain observations Nonlinear estimation applying an unscented transformation in systems with correlated uncertain observations](/preview/png/4630983.png)
An approximation to the least squares filter is proposed for discrete signals whose evolution is governed by nonlinear functions, when the estimation is based on nonlinear observations with additive noise which can consist only of random noise; this uncertainty in the observation process is modelled by Bernoulli random variables which are correlated at consecutive time instants and are otherwise independent. The proposed recursive approximation is based on the unscented principle; successive applications of the unscented transformation to a suitable augmented state vector enable us to approximate the one-stage state and observation predictors from the state filter at the previous time instant. The performance of the proposed algorithm is compared with that of an extended algorithm in a numerical simulation example.
Journal: Applied Mathematics and Computation - Volume 217, Issue 20, 15 June 2011, Pages 7998–8009