This study discusses and compares the performance of R-adaptive extended Kalman filters (EKF) with different covariance matching techniques for a nanosatellite attitude estimation. A non-traditional approach is used for the estimation process where the TRIAD and an EKF are integrated to reduce the computational load. In order to make the EKF adaptive, covariance matching techniques are used with single scaling factor (SSF), multiple scaling factors (MSFs), and fading factors (FFs), which is an alternative approach to MSFs. To compare the performance of the proposed algorithms, one simulation is performed where a noise increment is applied to the x-axis magnetometer. As a result of the simulation, it is seen that MSF and FF approaches are superior to the SSF approach. On the other hand, no differences in performance are observed between the MSF and FF approaches.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    A Covariance Matching-Based Adaptive EKF for Nanosatellite Attitude Estimation


    Additional title:

    Sustainable aviat.


    Contributors:

    Conference:

    International Symposium On Sustainable Aviation ; 2022 ; Melbourne, VIC, Australia August 03, 2022 - August 05, 2022



    Publication date :

    2023-10-11


    Size :

    7 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




    Attitude and attitude rate estimation for a nanosatellite using SVD and UKF

    Cilden, Demet / Hajiyev, Chingiz / Soken, Halil Ersin | IEEE | 2015


    SVD-Aided EKF for Nanosatellite Attitude Estimation Based on Kinematic Relations

    Cilden-Guler, Demet / Hajiyev, Chingiz | Springer Verlag | 2023



    Advanced Micro/Nanosatellite Attitude Control Systems (ACS)

    Lappas, V. J. / Steyn, W. H. / Underwood, C. I. et al. | British Library Conference Proceedings | 2002