Novel filter algorithm of space-borne GPS orbit determination
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摘要: 针对传统EKF(Extended Kalman Filtering)算法应用于星载GPS(Global Positioning System)低轨卫星定轨时系统噪声方差初值不易确定的问题,提出了一种新的定轨滤波算法.该算法在非线性方程线性化过程中,在前一时刻滤波估值点进行线性化,从而得到扰动方程,并将该扰动方程引入到传统EKF进行滤波处理.该算法与传统EKF分别应用在星载GPS低轨卫星的定轨中,通过比较,结果表明改进的算法在一定程度上抑制了由于系统噪声方差阵选取偏差较大而引起的滤波发散现象,且对于系统噪声方差的初值选取有较强的鲁棒性.Abstract: When conventional EKF (extended Kalman filtering) algorithm was used in LEO (low earth orbit satellite) orbit determination by space-borne GPS (global positioning system). It is difficult to know the initial value of system noise variance. Therefore, the novel filter algorithm of orbit determination was proposed. In the new algorithm, the methods of linearization at the prior filtering estimate value was adopted during the linearization process of the nonlinear equations, and the disturbing equations were obtained, and then the disturbing equations were introduced in conventional EKF. Apply the EKF and the modified algorithm in LEO orbit determination based on space-borne GPS respectively, the results show the modified algorithm can restrain filter divergence of conventional EKF caused by the large deflection of system noise variance in a certain extent, and has better robustness to the selecting of initial value of system noise variance.
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