摘要
针对普通UKF(无迹卡尔曼滤波)测量更新方法的非线性近似精度相对较低,导致目标跟踪滤波精度和稳定性较低的问题,在单星对空间目标的天基仅测角跟踪滤波过程中,提出一种基于迭代测量更新方法的IUKF(迭代UKF)算法。通过在测量更新过程中提高非线性系统状态估计的近似精度,进而提高目标跟踪滤波精度,并引入具有全局收敛性的阻尼Gauss-Newton(高斯-牛顿)法来改进IUKF的数值稳定性。理论分析与实验结果表明,该方法不仅避免了求解雅可比矩阵和Hessian矩阵,而且具有较高的滤波精度和数值稳定性。
An IUKF （Iterated Unscented Kalman Filter） algorithm based on iterated measurement update method is proposed for use during single-satellite bearings only tracking of space objects to solve the problem of low object tracking filtering accuracy and stability because of low nonlinear approximation accuracy of conventional UKF meas- urement update methods. As a result of the increase of the approximation accuracy of nonlinear system states during measurement update, the accuracy of object tracking filter is increased. Furthermore, damping Gauss-Newton meth- od with global convergence is introduced to increase the numerical stability of IUKF. Theoretical analysis and simu- lation results show that IUKF has benefits such as avoiding calculation of Jacobian matrix and Hessian matrix be- sides having higher nonlinear approximation accuracy and numerical stability.
出处
《飞行器测控学报》
CSCD
2013年第3期257-261,共5页
Journal of Spacecraft TT&C Technology
基金
国家863基金资助项目(No.2007AA12Z308)
