An inertial sensor calibration platform to estimate and select error models

Roberto Molinari, James Balamuta, Stephane Guerrier, Jan Skaloud

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

A new open-source software platform that, among others, allows to select models for inertial sensor stochastic calibration is presented in this paper. This platform consists in a package included in the statistical software R. The identification of stochastic models and estimation of model parameters is based on the method of Generalized Method of Wavelet Moments. This approach provides an extremely general framework for the identification, estimation and testing of models to describe and predict the error signals coming from inertial sensors. With the possibility of estimating complex models made of the sum of different underlying processes, this paper also presents the method with which a model, or a restrict set of models, can be selected that best describes and predicts the error signal.

Original languageEnglish (US)
Title of host publication2015 International Association of Institutes of Navigation World Congress, IAIN 2015 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781467376341
DOIs
StatePublished - Dec 9 2015
Event15th World Congress of International Association of Institutes of Navigation, IAIN 2015 - Prague, Czech Republic
Duration: Oct 20 2015Oct 23 2015

Publication series

Name2015 International Association of Institutes of Navigation World Congress, IAIN 2015 - Proceedings

Other

Other15th World Congress of International Association of Institutes of Navigation, IAIN 2015
Country/TerritoryCzech Republic
CityPrague
Period10/20/1510/23/15

Keywords

  • Allan Variance
  • Error Analysis
  • Generalized Method of Wavelet Moments
  • Model Selection
  • Wavelet Variance

ASJC Scopus subject areas

  • Aerospace Engineering
  • Software
  • Electrical and Electronic Engineering
  • Computer Science Applications

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