A computational multivariate-based technique for inertial sensor calibration

Gaetan Bakalli, Ahmed Radi, Naser El-Sheimy, Roberto Molinari, Stéphane Guerrier

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

4 Scopus citations

Abstract

The task of inertial sensor calibration has become increasingly important due to the growing use of low-cost inertial measurement units which are however characterized by measurement errors. Being widely employed in a variety of mass-market applications, there is considerable focus on compensating for these errors by taking into account the deterministic and stochastic factors that characterize them. In this paper we focus on the stochastic part of the error signal where it is customary to register the latter and use the observed error signal to identify and estimate the stochastic models, often complex in nature, that underlie this process. However, it is often the case that these error signals are observed through a series of replicates for the same inertial sensor and equally often it can be noticed that these replicates have the same model structure but their parameters appear to be different between replicates. This phenomenon has not been taken into account by current stochastic calibration procedures which therefore can be conditioned by flawed parameter estimation. For this reason, this paper aims at delivering an approach that takes into account the parameter variation between replicates by delivering an estimator that minimizes a loss function that considers each replicate, thereby improving measurement precision on the long run, and allows to build a statistical test to determine the presence of parameter variation between replicates.

Original languageEnglish (US)
Title of host publication30th International Technical Meeting of the Satellite Division of the Institute of Navigation, ION GNSS 2017
PublisherInstitute of Navigation
Pages3028-3038
Number of pages11
ISBN (Electronic)9781510853317
DOIs
StatePublished - 2017
Event30th International Technical Meeting of the Satellite Division of the Institute of Navigation, ION GNSS 2017 - Portland, United States
Duration: Sep 25 2017Sep 29 2017

Publication series

Name30th International Technical Meeting of the Satellite Division of the Institute of Navigation, ION GNSS 2017
Volume5

Other

Other30th International Technical Meeting of the Satellite Division of the Institute of Navigation, ION GNSS 2017
CountryUnited States
CityPortland
Period9/25/179/29/17

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Science Applications
  • Electrical and Electronic Engineering

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