A New Estimation Algorithm from Measurements with Multiple-Step Random Delays and Packet Dropouts | Zendy

R. CaballeroÁguila | Zendy; A. HermosoCarazo | Zendy; J. LinaresPérez | Zendy

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A New Estimation Algorithm from Measurements with Multiple-Step Random Delays and Packet Dropouts

Author(s) -

R. CaballeroÁguila,

A. HermosoCarazo,

J. LinaresPérez

Publication year - 2010

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 - 10.1155/2010/258065

Subject(s) - covariance , bernoulli's principle , algorithm , mathematics , network packet , bounded function , bernoulli distribution , filter (signal processing) , computation , random variable , computer science , mathematical optimization , statistics , computer network , mathematical analysis , engineering , computer vision , aerospace engineering

The least-squares linear estimation problem using covarianceinformation is addressed in discrete-time linear stochasticsystems with bounded random observation delays which can lead tobounded packet dropouts. A recursive algorithm, including thecomputation of predictor, filter, and fixed-point smoother, isobtained by an innovation approach. The random delays aremodeled by introducing some Bernoulli random variables with knowndistributions in the system description. The derivation of theproposed estimation algorithm does not require full knowledge ofthe state-space model generating the signal to be estimated, butonly the delay probabilities and the covariance functions of theprocesses involved in the observation equation

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