Volume 46 Issue 7
Jul.  2020
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YANG Jing, WEI Ruoyu. Comparative study on information fusion methods in constellation distributed autonomous orbit determination[J]. Journal of Beijing University of Aeronautics and Astronautics, 2020, 46(7): 1345-1353. doi: 10.13700/j.bh.1001-5965.2019.0463(in Chinese)
Citation: YANG Jing, WEI Ruoyu. Comparative study on information fusion methods in constellation distributed autonomous orbit determination[J]. Journal of Beijing University of Aeronautics and Astronautics, 2020, 46(7): 1345-1353. doi: 10.13700/j.bh.1001-5965.2019.0463(in Chinese)

Comparative study on information fusion methods in constellation distributed autonomous orbit determination

doi: 10.13700/j.bh.1001-5965.2019.0463
Funds:

National Natural Science Foundation of China 61976013

More Information
  • Corresponding author: YANG Jing, E-mail:jing.yang@buaa.edu.cn
  • Received Date: 30 Aug 2019
  • Accepted Date: 22 Dec 2019
  • Publish Date: 20 Jul 2020
  • In order to ensure that the large-scale navigation constellation has autonomous operation capability and accurate position reference information with limited on-board computing capability and communication capability, the information fusion method of constellation distributed autonomous orbit determination based on hierarchical constellation is studied. Taking the Earth-Moon satellite joint constellation as the research object, covariance convex, covariance intersection and matrix weighting method and scalar weighting method in the sense of linear minimum variance are used to achieve fusion estimation of all sub-filters in distributed filter structure. The performance of various fusion algorithms was compared and analyzed. The simulation results show that, based on the constellation distributed autonomous orbit determination algorithm designed by variance amplifying technique, the orbit determination precision is high when covariance convex and matrix weighting method and scalar weighting method in the sense of linear minimum varianceare used, and the precision is equivalent to the centralized filtering precision, while the precision will get down when covariance intersection fusion is adopted because the optimal coefficient cannot be accurately searched.

     

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