基于在轨服务航天器的测角和测距信息，采用了一种基于容积法则进行数值逼近的容积卡尔曼滤波算法对空间碎片进行相对导航，解决了初始测量误差较大时容易丢失目标的问题。为了提高算法的适用范围，采用一种普适状态转移矩阵进行状态外推，避免了近圆轨道的限制，适用于任意类型的轨道。仿真结果表明，容积卡尔曼滤波比传统采用的扩展卡尔曼滤波在初始估计误差较大的情况下可以获得更高的滤波精度和更快的收敛速度,为今后的工程实施提供了理论上的依据。

For the problem of relative navigation for space debris, cubature Kalman filter have been introduced based on the angle measurements and range measurements of on-orbit servicing spacecraft which is a numerical approximation algorithm using cubature law, resolving the problem of target missing with the larger error of initial measurement. In order to improve the field of application, a universal variable state transition equation was adopted to extrapolate the state, avoiding the limitation of near-circle orbit type. The simulation results show that the cubature Kalman filter has higher filtering accuracy and faster convergence speed than traditional extended Kalman filter in the situation of the larger error of initial estimation, which provides a theoretical basis for the implementation of the project in future.