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作者:

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

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摘要:

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.

关键词:

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

作者机构:

  • [ 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

通讯作者信息:

  • [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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来源 :

IEEE Sensors Journal

ISSN: 1530-437X

年份: 2021

期: 8

卷: 21

页码: 9969-9982

4 . 3 0 0

JCR@2022

ESI学科: ENGINEERING;

ESI高被引阀值:87

JCR分区:1

被引次数:

WoS核心集被引频次:

SCOPUS被引频次: 7

ESI高被引论文在榜: 0 展开所有

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