Observability-Based Space Noncooperative Target Motion Estimation

This study proposes a complete method for estimating the relative motion parameters of noncooperative targets in space and analyzes the system observability for the optically autonomous relative navigation problem of noncooperative targets in space. First, using the installation offset of the onboard monocular camera, a relative navigation system model is established herein by observing the three feature points of the target using the line-of-sight direction of the feature points as the measurement information and combining the target's relative orbital dynamics, attitude kinematics, and dynamics. Second, the system observability is analyzed based on the system observability matrix and combined with the null-space theory. The conditions under which the system does not satisfy the observability are analyzed through the definition of observability. An iterative extended Kalman filter based on this system model is then derived to realize the complete estimation of the target relative position, relative velocity, target attitude, angular velocity, inertia ratio, and position of the feature points under the target body frame. Finally, the effect of the camera offset on the system observability is analyzed through a numerical simulation. The results verify that an appropriate camera offset can make the monocular relative navigation system fully observable. The only existing unobservable state variable is found at 0 camera offset.

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Publication Details

Journal
IEEE Transactions on Aerospace and Electronic Systems
Published
2024-09-13
DOI
https://doi.org/10.1109/taes.2024.3460756
Citations
8
Primary Topic
Advanced SAR Imaging Techniques
Type
article
Field-Weighted Citation Impact
10.39

Funders

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article

Observability-Based Space Noncooperative Target Motion Estimation

Dayi Wang, Bowen Sun, Yijie Zhang, Xuanying Zhou et al.
8 citations
IEEE Transactions on Aerospace and Electronic Systems
Advanced SAR Imaging Techniques
10.39
article

Observability-Based Space Noncooperative Target Motion Estimation

Dayi Wang, Bowen Sun, Yijie Zhang, Xuanying Zhou, Bowen Hou, Jiongqi Wang
article en
8 citations

Abstract

This study proposes a complete method for estimating the relative motion parameters of noncooperative targets in space and analyzes the system observability for the optically autonomous relative navigation problem of noncooperative targets in space. First, using the installation offset of the onboard monocular camera, a relative navigation system model is established herein by observing the three feature points of the target using the line-of-sight direction of the feature points as the measurement information and combining the target's relative orbital dynamics, attitude kinematics, and dynamics. Second, the system observability is analyzed based on the system observability matrix and combined with the null-space theory. The conditions under which the system does not satisfy the observability are analyzed through the definition of observability. An iterative extended Kalman filter based on this system model is then derived to realize the complete estimation of the target relative position, relative velocity, target attitude, angular velocity, inertia ratio, and position of the feature points under the target body frame. Finally, the effect of the camera offset on the system observability is analyzed through a numerical simulation. The results verify that an appropriate camera offset can make the monocular relative navigation system fully observable. The only existing unobservable state variable is found at 0 camera offset.

IEEE Transactions on Aerospace and Electronic SystemsVol. 61(2)
National University of Defense Technology (CN), China Academy of Space Technology (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 2%
Advanced SAR Imaging Techniques
10.39
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Observability-Based Space Noncooperative Target Motion Estimation — Dayi Wang, Bowen Sun, et al. · IEEE Transactions on Aerospace and Electronic Systems (2024) | TGRS Research Map | TGRS