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Nanosatellite Attitude Estimation from Vector Measurements Using SVD-Aided UKF Algorithm

Cilden D., Soken H. E., Hajiev C.

Metrology and Measurement Systems

2017

Vol. 24, nr 1

113--125

The integrated Singular Value Decomposition (SVD) and Unscented Kalman Filter (UKF) method can recursively estimate the attitude and attitude rates of a nanosatellite. At first, Wahba’s loss function is minimized using the SVD and the optimal attitude angles are determined on the basis of the magnetometer and Sun sensor measurements. Then, the UKF makes use of the SVD’s attitude estimates as measurement results and provides more accurate attitude information as well as the attitude rate estimates. The elements of “Rotation angle error covariance matrix” calculated for the SVD estimations are used in the UKF as the measurement noise covariance values. The algorithm is compared with the SVD and UKF only methods for estimating the attitude from vector measurements. Possible algorithm switching ideas are discussed especially for the eclipse period, when the Sun sensor measurements are not available.

Aerospace Blockset for Xcos - Open source tool for aerospace systems numerical computation and simulation

Zagórski P., Grega W.

Measurement Automation Monitoring

2015

Vol. 61, No. 12

551--554

Aerospace Blockset for Xcos is a free, open and extendible software tool for aerospace systems simulations. It is a part of the open source Scilab/Xcos simulation environment. It was envisioned as a tool that fills the gap between the free, single-purpose aerospace software (e.g.. Space Trajectory Analysis, etc.), and the very expensive professional tools (eg. AGI-STK, Matalb-Simulink). Aerospace Blockset provides wide capabilities and is available for free even for commercial use.