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High-Precision Cooperative Positioning for Satellite Formation System via Multi-Observation Fusion

  • Peng Cheng
  • , Xiaolei Li*
  • , Yinhao Ju
  • , Baizheng Huan
  • *Corresponding author for this work
  • School of Astronautics, Harbin Institute of Technology

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Due to the observation constraints, achieving the high-precision positioning of the satellite formation system remains a significant challenge. This paper proposes a multi-observation fusion positioning scheme for the satellite formation system, which can improve three-dimensional positioning accuracy by the inter-satellite cooperative ranging. Firstly, the pseudo-range observation and baseline observation models are presented to provide the observation data for the satellite formation system. Secondly, the multi-observation fusion positioning scheme is developed using the extended Kalman filter and the nonlinear least-squares method to integrate pseudo-range observation and baseline observation. Finally, numerical simulations are implemented to validate the effectiveness of fusion positioning for the satellite formation system, demonstrating that the proposed scheme effectively reduces positioning errors and achieves higher accuracy of three-dimensional positioning than the traditional method.

Original languageEnglish
Title of host publicationProceeding of the 2025 4th International Conference on Advanced Sensing and Intelligent Manufacturing, ASIM 2025
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798331554989
DOIs
StatePublished - 2025
Externally publishedYes
Event4th International Conference on Advanced Sensing and Intelligent Manufacturing, ASIM 2025 - Changzhou, China
Duration: 31 Oct 20252 Nov 2025

Publication series

NameProceeding of the 2025 4th International Conference on Advanced Sensing and Intelligent Manufacturing, ASIM 2025

Conference

Conference4th International Conference on Advanced Sensing and Intelligent Manufacturing, ASIM 2025
Country/TerritoryChina
CityChangzhou
Period31/10/252/11/25

Keywords

  • Integrated Positioning
  • Kalman Filter
  • Least Squares
  • Satellite Formation

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