A High-Accuracy GPS-Aided Coarse Alignment Method for MEMS-Based SINS

Yulong Huang, Zheng Zhang, Siyuan Du, Youfu Li*, Yonggang Zhang*

*Corresponding author for this work

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

82 Citations (Scopus)

Abstract

In order to improve the computational efficiency and alignment accuracy of a microelectromechanical system (MEMS)-based strap-down inertial navigation system (SINS), this article proposes a high-Accuracy global positioning system (GPS)-Aided coarse alignment method. The attitude matrix between current and initial body frames and the unknown gyro bias, accelerometer bias, and lever arm are jointly estimated based on the proposed closed-loop approach, where the attitude error and unknown parameters are jointly inferred based on the derived linear state-space model using the Kalman filter. Simulation and experimental results illustrate that the proposed GPS-Aided coarse alignment method can achieve better accuracy than existing state-of-The-Art coarse alignment methods for MEMS-based SINS.
Original languageEnglish
Article number9047950
Pages (from-to)7914-7932
JournalIEEE Transactions on Instrumentation and Measurement
Volume69
Issue number10
Online published26 Mar 2020
DOIs
Publication statusPublished - Oct 2020

Research Keywords

  • Closed-loop approach
  • inertial navigation
  • initial alignment
  • Kalman filter
  • microelectromechanical system (MEMS)

Fingerprint

Dive into the research topics of 'A High-Accuracy GPS-Aided Coarse Alignment Method for MEMS-Based SINS'. Together they form a unique fingerprint.

Cite this