The University of Southampton
University of Southampton Institutional Repository

Use of the Extended Kalman Filter for State Dependent Drift Estimation in Weakly Nonlinear Sensors

Chorti, Arsenia, Karatzas, Dimosthenis, White, Neil M. and Harris, Chris J. (2006) Use of the Extended Kalman Filter for State Dependent Drift Estimation in Weakly Nonlinear Sensors Sensor Letters, 4, (4), pp. 377-379.

Record type: Article


A number of mechanisms are responsible for the generation of reversible or irreversible drift in the response of a sensor. In this letter, we discuss three approaches for the identification of reversible state dependent drift in sensors through the use of the Extended Kalman Filter. We compare their performance by simulation and demonstrate their validity by estimating the drift of an accelerometer, modeled as a weakly nonlinear system.

PDF SENSLET2006_Chorti.pdf - Other
Download (251kB)

More information

Published date: December 2006
Keywords: Drift Estimation, Extended Kalman Filter, Nonlinear sensors, sensor modelling
Organisations: EEE, Southampton Wireless Group


Local EPrints ID: 263545
PURE UUID: 7213882d-e4cb-4019-8e05-87ff7636b8df
ORCID for Neil M. White: ORCID iD

Catalogue record

Date deposited: 19 Feb 2007
Last modified: 18 Jul 2017 07:44

Export record


Author: Arsenia Chorti
Author: Dimosthenis Karatzas
Author: Neil M. White ORCID iD
Author: Chris J. Harris

University divisions

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton:

ePrints Soton supports OAI 2.0 with a base URL of

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.