INS Fine Alignment with Low-Cost Gyroscopes: Adaptive Filters for Different Measurement Types

Itzik Klein, Yaakov Bar-Shalom

Research output: Contribution to journalArticlepeer-review

Abstract

Inertial navigation system stationary fine alignment process is a critical step in reducing the initial errors of the attitude and sensor biases. While many studies had been made for tactical grade systems, less attention was given to low-cost sensors, which are a major player in today's inertial sensors market. To fill this gap, a measurement strategy combining different INS aiding types is proposed, analyzed and compared using numerical simulations and field experiments. Additionally, an analytical linear observability analysis is made to support the numerical comparisons. Further, five types of adaptive Kalman filters with the proposed measurement strategy are compared to find the appropriate one to improve the alignment performance. The proposed measurement strategy can be used in other applications of stationary conditions such as land vehicles, robots or shoe-mounted inertial navigation systems.

Original languageEnglish
Article number9427485
Pages (from-to)79021-79032
Number of pages12
JournalIEEE Access
Volume9
DOIs
StatePublished - 2021

Bibliographical note

Publisher Copyright:
© 2013 IEEE.

Keywords

  • Extended Kalman filter
  • fine alignment
  • inertial sensors
  • zero velocity updates

ASJC Scopus subject areas

  • General Computer Science
  • General Materials Science
  • General Engineering

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