Receding-horizon unscented Kalman filter for satellite attitude estimation

Ryo Hirasawa, Yuta Nakajima, Masaki Takahashi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper proposes a new constrained attitude estimation method for a satellite to reduce the influence of non-Gaussian measurement noise. A conventional constrained filter, the Receding-Horizon Nonlinear Kaiman Filter (RNKF), propagates the state value with a model in the prediction step, and minimizes the cost function with a constraint in the filtering step. The cost function is desired to be a quadratic program problem, whose constraint is linear, in terms of computational complexity. If the RNKF is applied to the attitude estimation problem, the appropriate attitude representation is the quaternion, which does not have a singular point, in the prediction step. However, the quaternion does not define a quadratic program in the filtering step because the quaternion needs to satisfy a single constraint of a unit norm. Therefore, this paper proposes the Receding-Horizon Unscented Kaiman Filter (RUKF) as an improvement of the RNKF to deal with appropriate attitude representation in each step. In the RUKF. the attitude is represented by the Rodrigues parameter in the filtering step owing to the Unscented Transformation. The Rodrigues parameter is an attitude representation with no constraint. It was confirmed from Monte Carlo simulation that the RUKF with a constraint is more accurate than the Extended Kaiman Filter.

Original languageEnglish
Title of host publicationProceedings of the International Astronautical Congress, IAC
PublisherInternational Astronautical Federation, IAF
Pages4963-4970
Number of pages8
Volume7
ISBN (Print)9781634399869
Publication statusPublished - 2014
Event65th International Astronautical Congress 2014: Our World Needs Space, IAC 2014 - Toronto, Canada
Duration: 2014 Sep 292014 Oct 3

Other

Other65th International Astronautical Congress 2014: Our World Needs Space, IAC 2014
CountryCanada
CityToronto
Period14/9/2914/10/3

Fingerprint

Kalman filters
Kalman filter
horizon
Satellites
filter
nonlinear filters
Cost functions
quaternions
filters
Computational complexity
costs
noise measurement
predictions
norms
estimation method
prediction
cost
simulation

ASJC Scopus subject areas

  • Space and Planetary Science
  • Aerospace Engineering
  • Astronomy and Astrophysics

Cite this

Hirasawa, R., Nakajima, Y., & Takahashi, M. (2014). Receding-horizon unscented Kalman filter for satellite attitude estimation. In Proceedings of the International Astronautical Congress, IAC (Vol. 7, pp. 4963-4970). International Astronautical Federation, IAF.

Receding-horizon unscented Kalman filter for satellite attitude estimation. / Hirasawa, Ryo; Nakajima, Yuta; Takahashi, Masaki.

Proceedings of the International Astronautical Congress, IAC. Vol. 7 International Astronautical Federation, IAF, 2014. p. 4963-4970.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Hirasawa, R, Nakajima, Y & Takahashi, M 2014, Receding-horizon unscented Kalman filter for satellite attitude estimation. in Proceedings of the International Astronautical Congress, IAC. vol. 7, International Astronautical Federation, IAF, pp. 4963-4970, 65th International Astronautical Congress 2014: Our World Needs Space, IAC 2014, Toronto, Canada, 14/9/29.
Hirasawa R, Nakajima Y, Takahashi M. Receding-horizon unscented Kalman filter for satellite attitude estimation. In Proceedings of the International Astronautical Congress, IAC. Vol. 7. International Astronautical Federation, IAF. 2014. p. 4963-4970
Hirasawa, Ryo ; Nakajima, Yuta ; Takahashi, Masaki. / Receding-horizon unscented Kalman filter for satellite attitude estimation. Proceedings of the International Astronautical Congress, IAC. Vol. 7 International Astronautical Federation, IAF, 2014. pp. 4963-4970
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