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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。
Based on the angle measurement and ranging information of on-orbit service spacecraft, a volume-based Kalman filter algorithm based on volumetric principle is adopted for relative navigation of space debris, which solves the problem of easily losing the target when the initial measurement error is large . In order to improve the application of the algorithm, a universal state transition matrix is adopted to extrapolate the state, which avoids the limitation of near circular orbit and is suitable for any type of orbit. The simulation results show that the volume Kalman filter can get higher filtering accuracy and faster convergence rate than the traditional Extended Kalman Filter in the case of large initial estimation error, which provides a theoretical basis for the future project implementation .