中文摘要：

针对自主导航过程中不确定的测量噪声和干扰的影响,提出了一种具有自适应能力的状态估计方法———ASUKF方法.该方法对非线性的状态方程进行超球面分布UT变换,对非线性的测量方程求取雅可比矩阵,同时在滤波迭代过程中引入自适应因子,从而在保持估计精度的条件下,降低了UKF算法的计算量,并使滤波器具有了自适应能力.将ASUKF方法应用于自主导航系统导航信息的估计过程中,仿真结果表明：其在保持导航信息估计精度的同时,提高了估计效率,克服了自主导航过程中不确定的噪声和随机干扰的影响.

英文摘要：

In order to overcome uncertain noise and disturbance during autonomous spacecraft navigation,a state estimation method known as angmented state unscented kalman filter（ASUKF） having adaptive ability was presented.This method applied spherical simplex unscented transformation in the nonlinear state equation,calculated the Jacobian matrix in the nonlinear measurement equation,and introduced the adaptive factor during the filtering process.This was done to keep estimation precision the same as unscented kalman filter（UKF）,reduce scalar calculation,and improve the adaptive ability.Applying the ASUKF method to an autonomous navigation system through simulation shows that ASUKF not only retains estimate precision of navigational information,but also enhances estimation efficiency and has the ability to adapt to uncertain noises and random disturbances.