An optimal virtual inertial sensor framework using wavelet cross covariance

Yuming Zhang, Haotian Xu, Ahmed Radi, Roberto Molinari, Stephane Guerrier, Mucyo Karemera, Naser El-Sheimy

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

Abstract

The practice of inertial sensor calibration has commonly been carried out by taking into account the deterministic and stochastic components of the error measurements issued from a calibration session. Once the deterministic components have been taken into account through physical models, the remaining stochastic component has always been dealt with for each sensor separately. The latter process involves estimating complex probabilistic models for each sensor which has been proven to be extremely complicated over the past years, although recent proposals have allowed to overcome most of the limitations that have characterized this task. However, the separate stochastic calibration of the individual sensors composing an inertial measurement unit may not be wise in many cases since there can be considerable degrees of dependence between the sensors, especially between the gyroscopes. For this reason, there has been growing attention towards this issue in order to consider the influence of the stochastic behaviour of the sensors on each other, with few proposals that address this problem. Among these proposals there has been the idea of integrating the information coming from the different gyroscopes so as to build a virtual gyroscope. In this paper we build on this idea and, using a recently proposed method for multivariate signal modelling, we deliver a general and flexible framework that allows to consider many different modelling options which provide the basis to construct a virtual sensor that optimally combines the information from the individual sensors and considerably improves navigation accuracy.

Original languageEnglish (US)
Title of host publication2018 IEEE/ION Position, Location and Navigation Symposium, PLANS 2018 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1342-1350
Number of pages9
ISBN (Electronic)9781538616475
DOIs
StatePublished - Jun 5 2018
Event2018 IEEE/ION Position, Location and Navigation Symposium, PLANS 2018 - Monterey, United States
Duration: Apr 23 2018Apr 26 2018

Publication series

Name2018 IEEE/ION Position, Location and Navigation Symposium, PLANS 2018 - Proceedings

Other

Other2018 IEEE/ION Position, Location and Navigation Symposium, PLANS 2018
CountryUnited States
CityMonterey
Period4/23/184/26/18

All Science Journal Classification (ASJC) codes

  • Automotive Engineering
  • Aerospace Engineering
  • Control and Optimization

Fingerprint Dive into the research topics of 'An optimal virtual inertial sensor framework using wavelet cross covariance'. Together they form a unique fingerprint.

Cite this