Repository logo

Infoscience

  • English
  • French
Log In
Logo EPFL, École polytechnique fédérale de Lausanne

Infoscience

  • English
  • French
Log In
  1. Home
  2. Academic and Research Output
  3. Journal articles
  4. Linear Estimation of Deterministic Accelerometer Errors
 
research article

Linear Estimation of Deterministic Accelerometer Errors

Burkhard, Julien
•
Sharma, Aman  
•
Skaloud, Jan  
July 10, 2024
Navigation-Journal Of The Institute Of Navigation

The deterministic errors of an accelerometer comprise the prevailing i) bias, ii) scale factor, and iii) non-orthogonality. Together, these errors result in a nonlinear measurement model, which is conventionally solved via an iterative nonlinear least-squares method. In contrast to the conventional approach, we propose a novel method to transform the above nonlinear model into a system of linear equations, resulting in an exact, closed-form solution of the deterministic errors. The developed mathematical formulations are first verified in a simulation set-ting, followed by a real-time implementation using Robot Operating System for small micro-electromechanical inertial measurement units.

  • Files
  • Details
  • Metrics
Type
research article
DOI
10.33012/navi.656
Scopus ID

2-s2.0-85199903216

Author(s)
Burkhard, Julien

École Polytechnique Fédérale de Lausanne

Sharma, Aman  

EPFL

Skaloud, Jan  

EPFL

Date Issued

2024-07-10

Published in
Navigation-Journal Of The Institute Of Navigation
Volume

71

Issue

3

Subjects

deterministic accelerometer error

•

least squares

•

linear systems

•

singular value decomposition

•

ESOLAB

•

topotraj

Note

This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

URL

Publisher website

https://navi.ion.org/content/71/3/navi.656
Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
CRYOS  
ESO  
FunderFunding(s)Grant NumberGrant URL

European Union

Marie Skłodowska-Curie

754354

Available on Infoscience
August 13, 2024
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/240704
Logo EPFL, École polytechnique fédérale de Lausanne
  • Contact
  • infoscience@epfl.ch

  • Follow us on Facebook
  • Follow us on Instagram
  • Follow us on LinkedIn
  • Follow us on X
  • Follow us on Youtube
AccessibilityLegal noticePrivacy policyCookie settingsEnd User AgreementGet helpFeedback

Infoscience is a service managed and provided by the Library and IT Services of EPFL. © EPFL, tous droits réservés