Unscented Filtering from Delayed Observations with Correlated Noises | Zendy

A. HermosoCarazo | Zendy; J. LinaresPérez | Zendy

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Unscented Filtering from Delayed Observations with Correlated Noises

Author(s) -

A. HermosoCarazo,

J. LinaresPérez

Publication year - 2009

Publication title -

mathematical problems in engineering

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.262

H-Index - 62

eISSN - 1026-7077

pISSN - 1024-123X

DOI - 10.1155/2009/681593

Subject(s) - bernoulli's principle , transformation (genetics) , nonlinear system , kalman filter , control theory (sociology) , state (computer science) , random noise , bernoulli distribution , mathematics , unscented transform , algorithm , noise (video) , sampling (signal processing) , computer science , random variable , statistics , artificial intelligence , engineering , extended kalman filter , filter (signal processing) , physics , computer vision , moving horizon estimation , image (mathematics) , aerospace engineering , chemistry , biochemistry , control (management) , quantum mechanics , gene

A filtering algorithm based on the unscented transformation is proposed to estimate the state of a nonlinear system from noisy measurements which can be randomly delayed by one sampling time. The state and observation noises are perturbed by correlated nonadditive noises, and the delay is modeled by independent Bernoulli random variables

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