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[期刊论文]

Rapid Initial Self-Alignment Method Using CMKF for SINS under Marine Mooring Conditions

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Author:

Pei, Fujun (Pei, Fujun.) | Yin, Shunan (Yin, Shunan.) | Yang, Su (Yang, Su.)

Indexed by:

EI

Abstract:

To address the initial self-alignment problem of strapdown inertial navigation system under marine mooring conditions, a rapid initial self-alignment method based on the constraint matrix Kalman filter (CMKF) is proposed in this paper. The novelties of this method are two-fold. First, based on the Lie group differential equation, a one-step direct self-alignment model without coarse alignment process is designed directly based on a special orthogonal group of rigid-body rotations. In addition, to improve the alignment accuracy, the sensor biases are augmented into the state matrix to be estimated and compensated during the alignment process. Second, because the state of the proposed model is a matrix containing a special orthogonal group, a CMKF is developed to ensure the estimated accuracy. And a Lagrange function is designed in the CMKF to maintain the orthogonality of the special orthogonal group during the filtering process. The simulation and experimental results demonstrate that the proposed method exhibits better performance than existing methods in alignment accuracy and time, which can achieve the self-alignment of SINS under marine mooring conditions. © 2001-2012 IEEE.

Keyword:

Mooring Marine navigation Orthogonal functions Alignment Differential equations Lie groups Inertial navigation systems Kalman filters

Author Community:

  • [ 1 ] [Pei, Fujun]Faculty of Information Technology, Beijing University of Technology, Beijing, China
  • [ 2 ] [Pei, Fujun]Engineering Research Center of DigitalCommunity, Ministry of Education, Beijing University of Technology, Beijing; 100124, China
  • [ 3 ] [Yin, Shunan]Faculty of Information Technology, Beijing University of Technology, Beijing, China
  • [ 4 ] [Yang, Su]Faculty of Information Technology, Beijing University of Technology, Beijing, China

Reprint Author's Address:

  • [pei, fujun]engineering research center of digitalcommunity, ministry of education, beijing university of technology, beijing; 100124, china;;[pei, fujun]faculty of information technology, beijing university of technology, beijing, china

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Related Article:

Source :

IEEE Sensors Journal

ISSN: 1530-437X

Year: 2021

Issue: 8

Volume: 21

Page: 9969-9982

4 . 3 0 0

JCR@2022

ESI HC Threshold:87

JCR Journal Grade:1

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count: 7

30 Days PV: 0

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