基于EKF和EKPF的非合作空间目标单眼姿态估计

Zeming Jin, Ling Wang, Hanhan Liu, Ronghua Du, Xiang Zhang
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引用次数: 0

摘要

基于视觉的相对姿态估计被广泛应用于各种空间导航任务中。针对航天器自主逼近未知非合作目标时的相对位姿估计问题,提出了一种基于扩展卡尔曼滤波和扩展卡尔曼粒子滤波的单眼非合作空间目标位姿估计方法。与现有方法相比,该方法不依赖于目标的大小、形状等先验信息,仅使用目标图像特征点的坐标作为滤波输入,实现了对所有位姿参数的快速、准确估计。仿真结果验证了该方法的有效性和可行性。
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Monocular-Based Pose Estimation of Non-Cooperative Space Targets Using EKF and EKPF
Relative pose estimation based on vision is widely used in various space navigation tasks. Considering the relative pose estimation problem of a spacecraft autonomous approaching to an unknown and non-cooperative target, a method for monocular-based pose estimation of non-cooperative space targets using Extended Kalman filter (EKF) and Extended Kalman Particle Filter (EKPF) is proposed. Compared with the existing methods, the proposed method does not depend on the prior information such as the size and shape of the target, and only uses the coordinates of the feature points of the target image as the filter input to realize the fast and accurate estimation of all pose parameters. Simulation results verify the effectiveness and feasibility of the proposed method.
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