Strong tracking unscented Kalman filter algorithm based-on satellite attitude determination system

When the satellite attitude determination system is disturbed by uncertain factors, square-root unscented Kalman filter (SRUKF) is featured by low accuracy, bad tracking ability and poor robustness. In order to overcome these defects of SRUKF, an improved strong tracking squared-root Kalman filter (ISTSRUKF) based-on satellite attitude determination system was proposed. To avoid calculating the Jacobian matrices, the fading factors were calculated by using equivalent description of fading factors. To ensure the symmetry of covariance matrix, two multiple fading factors matrices were introduced. To improve the stability of filter, a modified square-root decomposition method was adopted. The simulation results show that improved strong tracking square root UKF has best stability, robustness and mutation status tracking capability than square-root UKF and strong tracking filter.