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Elastic Modulus Estimation Using a Scaled State Parameter in the Extended Kalman Filter

Koch, M. C. / Murakami, A. / Fujisawa, K.

Abstract The Elastic Modulus of soil is an important property both from a strength and settlement perspective. Back analysis using observation data in an EKF could prove troublesome considering the large difference in magnitude of the covariances of the observation noise and the state vector noise. A simple scaled formulation is developed wherein the Kalman Filtering is done with respect to a new scaled state parameter. The domain is subdivided into blocks and only a simple two-block case is considered. The Elastic Modulus is considered constant inside a block. The EKF using the scaled state parameter is successful in estimating the state of only one of the blocks.

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Elastic Modulus Estimation Using a Scaled State Parameter in the Extended Kalman Filter

Koch, M. C. / Murakami, A. / Fujisawa, K.

Abstract The Elastic Modulus of soil is an important property both from a strength and settlement perspective. Back analysis using observation data in an EKF could prove troublesome considering the large difference in magnitude of the covariances of the observation noise and the state vector noise. A simple scaled formulation is developed wherein the Kalman Filtering is done with respect to a new scaled state parameter. The domain is subdivided into blocks and only a simple two-block case is considered. The Elastic Modulus is considered constant inside a block. The EKF using the scaled state parameter is successful in estimating the state of only one of the blocks.

Elastic Modulus Estimation Using a Scaled State Parameter in the Extended Kalman Filter

Koch, M. C. / Murakami, A. / Fujisawa, K.

Abstract The Elastic Modulus of soil is an important property both from a strength and settlement perspective. Back analysis using observation data in an EKF could prove troublesome considering the large difference in magnitude of the covariances of the observation noise and the state vector noise. A simple scaled formulation is developed wherein the Kalman Filtering is done with respect to a new scaled state parameter. The domain is subdivided into blocks and only a simple two-block case is considered. The Elastic Modulus is considered constant inside a block. The EKF using the scaled state parameter is successful in estimating the state of only one of the blocks.

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Title:

Elastic Modulus Estimation Using a Scaled State Parameter in the Extended Kalman Filter

Contributors:

Koch, M. C. (author) / Murakami, A. (author) / Fujisawa, K. (author)

Published in:

Geotechnics for Natural Disaster Mitigation and Management ; 43-51

Developments in Geotechnical Engineering

Publication date:

2019-08-20

Size:

9 pages

ISBN:

978-981-13-8828-6 , 978-981-13-8827-9

ISSN:

2364-5156 , 2364-5164

DOI:

https://doi.org/10.1007/978-981-13-8828-6_4

Type of media:

Article/Chapter (Book)

Type of material:

Electronic Resource

Language:

English

Keywords:

Elastic modulus , EKF , Scaled state parameter Engineering , Geoengineering, Foundations, Hydraulics , Geotechnical Engineering & Applied Earth Sciences , Urban Geography / Urbanism (inc. megacities, cities, towns)

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