Conservative Term Constrained Kalman Filter for Autonomous Orbit Determination

Zhai Guang*, Li Yuyang, Bi Xingzi

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

8 Citations (Scopus)

Abstract

This paper presents a novel constrained Kalman filter framework for autonomous orbit determination. By using Lagrangian multiplier techniques, the conserved terms of orbit motion are incorporated into the estimation routines to reconstruct the Kalman filter, and then the orthogonal and multipartial-norm-constrained Kalman filters are developed for the satellite in circular orbit and eccentric ones, respectively. Finally, scenarios of both circular and eccentric orbits with unknown measurement bias are simulated by using the proposed constrained Kalman filter; the simulation results show that the estimation accuracy is significantly improved after introducing the conservative terms as constraint.

Original languageEnglish
Pages (from-to)783-793
Number of pages11
JournalIEEE Transactions on Aerospace and Electronic Systems
Volume54
Issue number2
DOIs
Publication statusPublished - Apr 2018

Keywords

  • Autonomous navigation
  • Kalman filter (KF)
  • constraints
  • earth and star sensor
  • orbit determination

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