Journal of Astronautics ›› 2021, Vol. 42 ›› Issue (9): 1128-1138.doi: 10.3873/j.issn.1000-1328.2021.09.008

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A Parameterized Method to Estimate Relative Pose and Inertia Information of a Non cooperative Target

FENG Qian, PAN Quan, HOU Xiao lei, YANG Jia nan   

  1. 1. School of Automation, Northwestern Polytechnical University, Xi’an 710072, China;2. Key Laboratory of Information Fusion Technology Ministry of Education, Northwestern Polytechnical University, Xi’an 710072, China

  • Received:2020-10-09 Revised:2021-01-22 Online:2021-09-15 Published:2021-09-15

Abstract: Aiming at solving the problem that space non cooperative targets, such as malfunctioning satellites, failed spacecraft and space debris, do not have a priori information for directly obtaining their models, inertia parameters and inertial angular velocities, a parameterized method based on stereo vision is proposed to estimate a non cooperative target’s pose and inertia information. Based on the equation of attitude dynamics for a free spacecraft, the inverse hyperbolic tangent functions with two independent variables are adopted to parameterize the inertia ratios of the non cooperative target, then the angular velocity propagation equation of the target is established. Measurement equations are established for the non cooperative target using several feature points acquired from the stereo vision measurement system. Whereafter, combined with the relative kinematics model described by Clohessy Wiltshire equation, an extended Kalman filter is designed to estimate the state, including the relative position, relative linear velocity, relative attitude, inertial angular velocity and inertia parameters of the non cooperative target. Finally, the performance of the proposed algorithm is investigated using numerical simulation in different scenarios. The Monte Carlo simulation results demonstrate that the designed filter can effectively estimate the relative pose and inertia parameters of the non cooperative target with high accuracy in various levels of measurement noise.

Key words: Stereo vision, Non cooperative targets, Relative pose, Inertia parameters, State estimation, Extended Kalman filter

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