Particle filter with novel nonlinear error model for miniature gyroscope-based measurement while drilling navigation

Tao Li, Gannan Yuan, Wang Li

Research output: Contribution to journalArticlepeer-review

15 Citations (Scopus)

Abstract

The derivation of a conventional error model for the miniature gyroscope-based measurement while drilling (MGWD) system is based on the assumption that the errors of attitude are small enough so that the direction cosine matrix (DCM) can be approximated or simplified by the errors of small-angle attitude. However, the simplification of the DCM would introduce errors to the navigation solutions of the MGWD system if the initial alignment cannot provide precise attitude, especially for the low-cost microelectromechanical system (MEMS) sensors operated in harsh multilateral horizontal downhole drilling environments. This paper proposes a novel nonlinear error model (NNEM) by the introduction of the error of DCM, and the NNEM can reduce the propagated errors under large-angle attitude error conditions. The zero velocity and zero position are the reference points and the innovations in the states estimation of particle filter (PF) and Kalman filter (KF). The experimental results illustrate that the performance of PF is better than KF and the PF with NNEM can effectively restrain the errors of system states, especially for the azimuth, velocity, and height in the quasi-stationary condition.

Original languageEnglish
Article number371
JournalSensors (Switzerland)
Volume16
Issue number3
DOIs
Publication statusPublished - 2016 Mar 15
Externally publishedYes

Keywords

  • MEMS
  • MGWD
  • Multilateral horizontal drilling
  • NNEM
  • PF
  • Quasi-stationary condition

ASJC Scopus subject areas

  • Analytical Chemistry
  • Biochemistry
  • Atomic and Molecular Physics, and Optics
  • Instrumentation
  • Electrical and Electronic Engineering

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