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

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.

[1]  I.M. Ross,et al.  NPSAT1 Parameter Estimation Using Unscented Kalman Filtering , 2007, 2007 American Control Conference.

[2]  H.F. Durrant-Whyte,et al.  A new approach for filtering nonlinear systems , 1995, Proceedings of 1995 American Control Conference - ACC'95.

[3]  Yuya Mimasu,et al.  Attitude Determination Concept for QSAT , 2009 .

[4]  A. Solís-Santomé,et al.  Attitude Determination System Based on Vector Observations for Satellites Experiencing Sun-Eclipse Phases , 2015 .

[5]  Felipe Espinosa,et al.  Adaptive UAV Attitude Estimation Employing Unscented Kalman Filter, FOAM and Low-Cost MEMS Sensors , 2012, Sensors.

[6]  Ch. Hajiyev,et al.  Attitude determination and control system design of the ITU-UUBF LEO1 satellite , 2003 .

[7]  Grace Wahba,et al.  Problem 65-1: A least squares estimate of satellite attitude , 1966 .

[8]  M. Shuster,et al.  Complete linear attitude-independent magnetometer calibration , 2002 .

[9]  Pol D. Spanos,et al.  Q-Method Extended Kalman Filter , 2015 .

[10]  Melanie Hartmann,et al.  Spacecraft Attitude Determination And Control , 2016 .

[11]  E. Glenn Lightsey,et al.  Sequential Optimal Attitude Recursion Filter , 2010 .

[12]  A. Chulliat,et al.  International Geomagnetic Reference Field: the eleventh generation , 2010 .

[13]  D. Vallado.  Fundamentals of Astrodynamics and Applications , 1997 .

[14]  James Cutler,et al.  Flight results of a low-cost attitude determination system , 2014 .

[15]  Jesper Abildgaard Larsen,et al.  Inexpensive CubeSat Attitude Estimation Using Quaternions and Unscented Kalman Filtering , 2011 .

[16]  F. Landis Markley,et al.  Attitude Determination Using Two Vector Measurements , 1998 .

[17]  F. Markley,et al.  Quaternion Attitude Estimation Using Vector Observations , 2000 .

[18]  Yaakov Oshman,et al.  Spacecraft Angular Velocity Estimation Using Sequential Observations of a Single Directional Vector , 2003 .

[19]  Tomohiro Narumi,et al.  Attitude Determination by Magnetometer and Gyros During Eclipse , 2008 .

[20]  Wei Quan,et al.  Interlaced optimal-REQUEST and unscented Kalman filtering for attitude determination , 2013 .

[21]  Mark L. Psiaki,et al.  N 8 9 - 1 5 9 5 1 Three-Axis Attitude Determination via Kalman Filtering of Magnetometer Data , 2003 .

[22]  F. Markley,et al.  Unscented Filtering for Spacecraft Attitude Estimation , 2003 .

[23]  Halil Ersin Soken,et al.  Attitude and attitude rate estimation for a nanosatellite using SVD and UKF , 2015, 2015 7th International Conference on Recent Advances in Space Technologies (RAST).

[24]  Halil Ersin Soken,et al.  UKF-Based Reconfigurable Attitude Parameters Estimation and Magnetometer Calibration , 2012, IEEE Transactions on Aerospace and Electronic Systems.