Use of the extended Kalman filter for state dependent drift estimation in weakly nonlinear sensors

Arsenia Chorti; Dimosthenis Karatzas; Neil M. White; Chris J. Harris

doi:10.1166/sl.2006.051

Use of the extended Kalman filter for state dependent drift estimation in weakly nonlinear sensors

Arsenia Chorti^*, Dimosthenis Karatzas, Neil M. White, Chris J. Harris

^*Corresponding author for this work

Department of Computer Science

Research output: Contribution to journal › Article › Research › peer-review

3 Citations (Scopus)

Abstract

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.

Original language	English
Pages (from-to)	377-379
Number of pages	3
Journal	Sensor Letters
Volume	4
Issue number	4
DOIs	https://doi.org/10.1166/sl.2006.051
Publication status	Published - Dec 2006

Keywords

EKF-based drift estimators
Gaussian state variables
Sinusoidal state variable

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10.1166/sl.2006.051

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title = "Use of the extended Kalman filter for state dependent drift estimation in weakly nonlinear sensors",

abstract = "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.",

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AU - Chorti, Arsenia

AU - Karatzas, Dimosthenis

AU - White, Neil M.

AU - Harris, Chris J.

PY - 2006/12

Y1 - 2006/12

N2 - 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.

AB - 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.

KW - EKF-based drift estimators

KW - Gaussian state variables

KW - Sinusoidal state variable

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U2 - 10.1166/sl.2006.051

DO - 10.1166/sl.2006.051

M3 - Article

AN - SCOPUS:33847693567

SN - 1546-198X

VL - 4

SP - 377

EP - 379

JO - Sensor Letters

JF - Sensor Letters

IS - 4

ER -

Use of the extended Kalman filter for state dependent drift estimation in weakly nonlinear sensors

Abstract

Keywords

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