An observability analysis method of deep space autonomous navigation system

Xiao Hua Chang*, Ping Yuan Cui, Hu Tao Cui

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)

Abstract

For the observability of nonlinear system, the observability matrix was derived using the Lie differentiation combining with the correlation theory of differential geometry, and an analytic method to measure the observability degree of nonlinear system was given. Then the method was applied in the observability analysis of deep space autonomous navigation system based on the Sun line-of-sight vector. The variations of observability degree for different orbital elements were investigated. Furthermore, in order to verify the relation between the observability degree and the estimation accuracy of the navigation system, the navigation process under different observability degrees was performed based on the extended Kalman filter. The method of the observability analysis proposed in this paper was demonstrated to be feasible from simulation results.

Original languageEnglish
Pages (from-to)1681-1685
Number of pages5
JournalHarbin Gongye Daxue Xuebao/Journal of Harbin Institute of Technology
Volume42
Issue number11
Publication statusPublished - Nov 2010

Keywords

  • Autonomous navigation
  • Nonlinear system
  • Observability

Fingerprint

Dive into the research topics of 'An observability analysis method of deep space autonomous navigation system'. Together they form a unique fingerprint.

Cite this