Attitude error estimation and coupled filter integration

Esit M., SÖKEN H. E.

ACTA ASTRONAUTICA, cilt.251, ss.388-399, 2027 (SCI-Expanded, Scopus)

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 251
  • Basım Tarihi: 2027
  • Doi Numarası: 10.1016/j.actaastro.2026.10.003
  • Dergi Adı: ACTA ASTRONAUTICA
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Compendex, INSPEC, Public Affairs Index, Academic Search Ultimate (EBSCO)
  • Sayfa Sayıları: ss.388-399
  • Orta Doğu Teknik Üniversitesi Adresli: Evet

Özet

Integrating the attitude filter with one of the static attitude determination methods, such as QUEST, is a method that has several practical advantages. These advantages include but are not limited to quick convergence, fusing multiple vector measurements in a computationally efficient way, and providing contingency solutions for star trackers. When star tracker quaternion measurements are used in the attitude filter, the overall architecture becomes similar, too. First, this article provides an overview of attitude error estimation based on Wahba's problem, examining both an eigenvalue-based formulation and an alternative algebraic approach. This attitude error estimation builds the foundation for a coupled filtering approach proposed in the latter part of the article. The attitude error estimation algorithm is integrated with the filter in the error domain so that it estimates the attitude error. The proposed approach simplifies the overall algorithm while still preserving the advantages of static attitude determination and filtering integration, such as quick convergence. It also provides an alternative for autonomous star trackers' quaternion estimation algorithms when fed with the gyro measurements. Finally, the attitude filtering performance with the three approximations of the maximum eigenvalue involved in this proposed attitude error estimation formulation is compared. Numerical simulations, including a Monte Carlo robustness analysis, show that the approximation lambda(0) achieves the best overall robustness while being the fastest to compute.