基于IUKF的单星对空间目标仅测角跟踪算法

摘要

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 measurement 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 method with global convergence is introduced to increase the numerical stability of IUKF.Theoretical analysis and simulation results show that IUKF has benefits such as avoiding calculation of Jacobian matrix and Hessian matrix besides having higher nonlinear approximation accuracy and numerical stability.%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.