Deriving Kalman Filter – An Easy Algorithm

Article ID

R201C

Deriving Kalman Filter – An Easy Algorithm

Amaresh Das
Amaresh Das University of New Orleans
Faisal Alkhateeb
Faisal Alkhateeb
DOI

Abstract

The Kalman filter may be easily understood by the econometricians, and forecasters if it is cast as a problem in Bayesian inference and if along the way some well-known results in multivariate statistics are employed. The aim is to motivate the readers by providing an exposition of the key notions of the predictive tool and by laying its derivation in a few easy steps. The paper does not deal with many other ad hoc techniques used in adaptive Kalman filtering.

Deriving Kalman Filter – An Easy Algorithm

The Kalman filter may be easily understood by the econometricians, and forecasters if it is cast as a problem in Bayesian inference and if along the way some well-known results in multivariate statistics are employed. The aim is to motivate the readers by providing an exposition of the key notions of the predictive tool and by laying its derivation in a few easy steps. The paper does not deal with many other ad hoc techniques used in adaptive Kalman filtering.

Amaresh Das
Amaresh Das University of New Orleans
Faisal Alkhateeb
Faisal Alkhateeb

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Amaresh Das. 2017. “. Global Journal of Science Frontier Research – F: Mathematics & Decision GJSFR-F Volume 17 (GJSFR Volume 17 Issue F3): .

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Crossref Journal DOI 10.17406/GJSFR

Print ISSN 0975-5896

e-ISSN 2249-4626

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GJSFR-F Classification: MSC 2010: 11Y16
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Deriving Kalman Filter – An Easy Algorithm

Amaresh Das
Amaresh Das University of New Orleans
Faisal Alkhateeb
Faisal Alkhateeb

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