基于序列图像的航天器自主导航降维滤波方法

非合作目标的运动感知与状态估计，是太空领域技术发展的重要组成部分。非合作目标相对状态的精确估计是相对导航的难点问题。传统的非合作目标扩展卡尔曼滤波算法需要结合非合作目标的质心位置，增加了状态变量的维数，提高了系统不确定性，从而会影响状态扩展卡尔曼滤波的收敛速度。提出了一种基于序列图像的非合作目标相对导航方法，该方法在不对质心进行估计的情况下首先对非合作目标姿态进行估计，在完成非合作目标姿态估计后再对其质心进行估计。本文推导了光学相机测量值与目标真实姿态的关系，构建了基于序列图像的测量模型，分别建立了不含有非合作目标质心位置的状态方程和基于非合作目标位置、速度矢量的状态方程，设计了适用于非合作目标状态估计的扩展卡尔曼滤波算法。仿真实验表明该方法可在10 Hz采样频率下经过50次采样（即5 s）内快速收敛，从而有利于空间飞行器的在轨服务与维护。

Filter method for dimension reduction in spacecraft autonomous navigation based on sequence image

Motion measurement and state estimation of the non-cooperative target play an important role in the development of space technology. Estimation of the relative state of the non-cooperative target is a difficult problem. In the traditional extended Kalman filter algorithm, it is needed to estimate the centroid position of the non-cooperative target, which increases the dimension of state variables and uncertainty of the system, and thus affects the convergence speed of extended Kalman filtering. In this paper, a relative navigation method for non-cooperative target based on the sequence image is proposed. The attitude estimation of non-cooperative target can be realized without estimation of the centroid position, then the centroid position can be estimated based on the attitude estimated before. The relationship between the measured value and the true attitude of the non-cooperative target is derived. The sequence-image based measurement model is constructed. The state formula without the centroid position of the non-cooperative target and the state formula based on the position and velocity of non-cooperative target are established. An extended Kalman filter algorithm for state estimation of the non-cooperative target is developed. It is shown that the proposed method can converge rapidly within 50 samples times (i.e., 5 seconds) at a sampling frequency of 10HZ in the simulation, and is thus beneficial to the on-orbit service and maintenance of space vehicles.