TY - JOUR
T1 - Relative State and Inertia Estimation of Unknown Tumbling Spacecraft by Stereo Vision
AU - Feng, Qian
AU - Zhu, Zheng H.
AU - Pan, Quan
AU - Hou, Xiaolei
N1 - Publisher Copyright:
© 2013 IEEE.
PY - 2018
Y1 - 2018
N2 - A novel algorithm is proposed to estimate the relative state, including position, attitude, linear velocity, angular velocity, and inertia parameters of an unknown tumbling spacecraft, by stereo vision. Feature points of the target are selected in situ, and their positions and velocities are estimated by the measurements of perspective projection and optical flow. Then, the relative attitude and angular velocity of the spacecraft are estimated by a unit quaternion method and least square method, respectively. After that, the relative position and translational velocity of the spacecraft, together with the relative positions of the detected feature points, are estimated simultaneously based on the relative translational motion model of the target by successive images. Finally, inertia parameters of the spacecraft are estimated by a quadratic optimization method based on angular momentum conservation subject to physical constraints. The performance of the newly proposed algorithm is verified by comparing with an existing case in the literature. Moreover, the performance is validated by Monte-Carlo simulations in different cases.
AB - A novel algorithm is proposed to estimate the relative state, including position, attitude, linear velocity, angular velocity, and inertia parameters of an unknown tumbling spacecraft, by stereo vision. Feature points of the target are selected in situ, and their positions and velocities are estimated by the measurements of perspective projection and optical flow. Then, the relative attitude and angular velocity of the spacecraft are estimated by a unit quaternion method and least square method, respectively. After that, the relative position and translational velocity of the spacecraft, together with the relative positions of the detected feature points, are estimated simultaneously based on the relative translational motion model of the target by successive images. Finally, inertia parameters of the spacecraft are estimated by a quadratic optimization method based on angular momentum conservation subject to physical constraints. The performance of the newly proposed algorithm is verified by comparing with an existing case in the literature. Moreover, the performance is validated by Monte-Carlo simulations in different cases.
KW - inertia parameters
KW - relative state estimation
KW - stereo vision
KW - Unknown tumbling spacecraft
UR - http://www.scopus.com/inward/record.url?scp=85054618249&partnerID=8YFLogxK
U2 - 10.1109/ACCESS.2018.2872039
DO - 10.1109/ACCESS.2018.2872039
M3 - 文章
AN - SCOPUS:85054618249
SN - 2169-3536
VL - 6
SP - 54126
EP - 54138
JO - IEEE Access
JF - IEEE Access
M1 - 8471167
ER -