QUEST Aided EKF for Attitude and Rate Estimation Using Modified Rodrigues Parameters

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Kinatas H., Hajiyev C.

WSEAS Transactions on Systems and Control, vol.17, pp.250-261, 2022 (Scopus) identifier

  • Publication Type: Article / Article
  • Volume: 17
  • Publication Date: 2022
  • Doi Number: 10.37394/23203.2022.17.29
  • Journal Name: WSEAS Transactions on Systems and Control
  • Journal Indexes: Scopus, INSPEC
  • Page Numbers: pp.250-261
  • Keywords: attitude estimation, magnetometer, modified Rodrigues parameters, Nanosatellite, QUEST, sun sensor
  • Istanbul Technical University Affiliated: Yes


© 2022, World Scientific and Engineering Academy and Society. All rights reserved.A conventional attitude estimation system for a nanosatellite involves direct input of the attitude sensor measurements to a Kalman filter. However, in case of using an extended Kalman filter (EKF) for the attitude filtering, frequent calculations of the Jacobian matrices bring an excessive computational burden which may not be practical for a nanosatellite on-board computer. In order to deal with this problem, in this study, a QUEST aided EKF attitude and attitude rate estimation system is proposed. QUEST algorithm is used to obtain an initial coarse attitude estimation and then, this estimation is filtered via an EKF. The proposed integrated system reduces the computational burden that an EKF brings since the direct input of the attitude measurements to the filter makes the measurement model linear. For the attitude representation, modified Rodrigues parameters (MRPs) are used unlike widely used quaternions due to the advantages they provide. MRP representation has a singularity at only at the multiples of 2π, therefore, any rotation can be represented by MRPs, except a complete 360∘ rotation. This singularity can be easily avoided switching between alternate MRP sets which is also discussed in this study. The performance of the proposed system is tested with several simulations and the results are presented together with the estimation errors and variances.