基于强跟踪的平方根 UKF 的卫星姿态确定算法

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

针对受不确定性干扰的影响卫星姿态确定系统,SRUKF存在跟踪能力弱、估计精度低和鲁棒性差等问题,本文根据强跟踪滤波(STF)原理,提出了一种改进的强跟踪平方根UKF算法。该方法中,采用基于等价变化的方法来计算自适应渐消因子,避免了Jacobian矩阵的计算;引入两个多重自适应渐消因子矩阵,保证了协方差矩阵的对称性;利用改进的平方根分解方法,改善了滤波器的稳定性。实验仿真结果表明,相对于SRUKF和STF,本文提出的强跟踪平方根UKF具有更好的稳定性、鲁棒性和对突变状态的跟踪能力。

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 Ja-cobian 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 im-prove the stability of filter, a modified square-root decomposition method was adopted. The simulation re-sults show that improved strong tracking square root UKF has best stability, robustness and mutation sta-tus tracking capability than square-root UKF and strong tracking filter.