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InECCE2019 pp 309-321 | Cite as

A Comparative Study of AFM-Assisted Direct and Least-Square Attitude Determination Algorithm

  • Suqing Yan
  • Yue Wu
  • Yuanfa JiEmail author
  • Kamarul Hawari Ghazali
  • Xiyan Sun
Conference paper
  • 27 Downloads
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 632)

Abstract

Based on GNSS (Global Navigation Satellite System) technology, the importance of vehicle attitude calculation has become more and more prominent in military and civilian fields. In this paper, an attitude determination algorithm assisted by ambiguity function method (AFM) is proposed. Due to the characteristics of the AFM algorithm is insensitive to cycle slip and independent of initial ambiguity, and considering the large amount of computation and the long computation time, it is used as an auxiliary means for initial attitude search and error correction in the search process, and C-LAMBDA algorithm is used to complete the ambiguity resolution. The attitude angle is calculated by direct and least square method, and the accuracy of the attitude angle based on the AFM-assisted method is compared. Through the static experiment of dual antenna direction finding and three antenna attitudes finding, the accuracy of direction and attitude angle is analyzed. It is concluded that the attitude calculation accuracy based on AFM-assisted least square method is usually higher.

Keywords

AFM The direct method Least square method 

Notes

Acknowledgements

This work has been supported by the following units and projects. They are the National Key R&D Program of China (2018YFB0505103), the National Natural Science Foundation of China (61561016, 61861008), Department of Science and Technology of Guangxi Zhuang Autonomous Region (AC16380014, AA17202048, AA17202033), Sichuan Science and Technology Plan Project (17ZDYF1495), Guilin Science and Technology Bureau Project (20160202, 20170216), the basic ability promotion project of young and middle-aged teachers in Universities of Guangxi province (ky2016YB164), the 2019 School-level Graduate Innovation Program (2019YCXS024).

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Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  • Suqing Yan
    • 1
    • 2
  • Yue Wu
    • 1
    • 2
  • Yuanfa Ji
    • 1
    • 2
    Email author
  • Kamarul Hawari Ghazali
    • 3
  • Xiyan Sun
    • 1
    • 2
  1. 1.Guangxi Key Laboratory of Precision Navigation Technology and ApplicationGuilin University of Electronic TechnologyGuilinChina
  2. 2.National & Local Joint Engineering Research Center of Satellite Navigation and Location ServiceGuilinChina
  3. 3.University Malaysia PahangPahangMalaysia

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