The Science and Information (SAI) Organization
  • Home
  • About Us
  • Journals
  • Conferences
  • Contact Us

Publication Links

  • IJACSA
  • Author Guidelines
  • Publication Policies
  • Digital Archiving Policy
  • Promote your Publication
  • Metadata Harvesting (OAI2)

IJACSA

  • About the Journal
  • Call for Papers
  • Editorial Board
  • Author Guidelines
  • Submit your Paper
  • Current Issue
  • Archives
  • Indexing
  • Fees/ APC
  • Reviewers
  • Apply as a Reviewer

IJARAI

  • About the Journal
  • Archives
  • Indexing & Archiving

Special Issues

  • Home
  • Archives
  • Proposals
  • Guest Editors
  • SUSAI-EE 2025
  • ICONS-BA 2025
  • IoT-BLOCK 2025

Future of Information and Communication Conference (FICC)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Computing Conference

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Intelligent Systems Conference (IntelliSys)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Future Technologies Conference (FTC)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact
  • Home
  • Call for Papers
  • Editorial Board
  • Guidelines
  • Submit
  • Current Issue
  • Archives
  • Indexing
  • Fees
  • Reviewers
  • Subscribe

DOI: 10.14569/IJACSA.2016.070557
PDF

Fault-Tolerant Fusion Algorithm of Trajectory and Attitude of Spacecraft Based on Multi-Station Measurement Data

Author 1: YANG Xiaoyan
Author 2: HU Shaolin
Author 3: YU Hui
Author 4: LI Shaomini Xi’an

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 7 Issue 5, 2016.

  • Abstract and Keywords
  • How to Cite this Article
  • {} BibTeX Source

Abstract: Aiming at the practical situation that the navigation processes of spacecrafts usually rely on several different kinds of tracking equipments which track the spacecraft by turns, a series of new outlier-tolerant fusion algorithms are build to determine the whole flight path as well as attitude parameters. In these new algorithms, the famous gradient descent methods are used to find out the outliers-tolerant flight paths from an integrated data-fusion function designed delicately. In this paper, these new algorithms are used to determine reliably the flight paths and attitude parameters in the situation that a spacecraft is tracked by a series of equipments working by turns and there are some outliers arising in the data series. Advantages of these new algorithms are not only plenary fusion of all of the data series from different kinds of equipments but also discriminatory usage: on the one hand, if the data are dependable, the useable information contained in these data are sufficiently used; on the other hand, if the data are outliers, the bad information from these data are efficiently eliminated from these algorithms. In this way, all of the computational flight paths and attitude parameters are insured to be consistent and reliable.

Keywords: trajectory; fault-tolerance; data fusion

YANG Xiaoyan, HU Shaolin, YU Hui and LI Shaomini Xi’an, “Fault-Tolerant Fusion Algorithm of Trajectory and Attitude of Spacecraft Based on Multi-Station Measurement Data” International Journal of Advanced Computer Science and Applications(IJACSA), 7(5), 2016. http://dx.doi.org/10.14569/IJACSA.2016.070557

@article{Xiaoyan2016,
title = {Fault-Tolerant Fusion Algorithm of Trajectory and Attitude of Spacecraft Based on Multi-Station Measurement Data},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2016.070557},
url = {http://dx.doi.org/10.14569/IJACSA.2016.070557},
year = {2016},
publisher = {The Science and Information Organization},
volume = {7},
number = {5},
author = {YANG Xiaoyan and HU Shaolin and YU Hui and LI Shaomini Xi’an}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

IJACSA

Upcoming Conferences

IntelliSys 2025

28-29 August 2025

  • Amsterdam, The Netherlands

Future Technologies Conference 2025

6-7 November 2025

  • Munich, Germany

Healthcare Conference 2026

21-22 May 2026

  • Amsterdam, The Netherlands

Computing Conference 2026

9-10 July 2026

  • London, United Kingdom

IntelliSys 2026

3-4 September 2026

  • Amsterdam, The Netherlands

Computer Vision Conference 2026

15-16 October 2026

  • Berlin, Germany
The Science and Information (SAI) Organization
BACK TO TOP

Computer Science Journal

  • About the Journal
  • Call for Papers
  • Submit Paper
  • Indexing

Our Conferences

  • Computing Conference
  • Intelligent Systems Conference
  • Future Technologies Conference
  • Communication Conference

Help & Support

  • Contact Us
  • About Us
  • Terms and Conditions
  • Privacy Policy

© The Science and Information (SAI) Organization Limited. All rights reserved. Registered in England and Wales. Company Number 8933205. thesai.org