Relative Motion Estimation Algorithm for Noncooperative Targets Considering Multiple Solutions of Rotational...

Area of Science:

• Robotics
• Spacecraft Engineering
• Computer Vision

Background:

• On-orbit servicing is crucial for space economics and safety.
• Estimating the relative motion of noncooperative targets presents significant challenges.
• Stereovision offers a promising approach for relative motion estimation.

Purpose of the Study:

• To develop a robust relative motion estimation scheme for noncooperative targets using stereovision.
• To address the challenge of multiple solutions in rotational parameter estimation.
• To accurately estimate full motion states and inertia parameters of targets.

Main Methods:

• Utilizing stereovision for relative motion estimation.
• Applying the least-square method and conservation of angular momentum to identify mass distribution.
• Resolving rotational ambiguities by determining a unique principal axis coordinate frame.
• Employing an extended Kalman filter (EKF) with global observability for state and parameter estimation.

Main Results:

• Successful estimation of relative motion states and inertia parameters for noncooperative targets.
• Demonstrated robustness of the proposed method against target occlusion.
• Verification of convergence performance through numerical simulations.

Conclusions:

• The developed stereovision-based scheme effectively estimates the motion of noncooperative targets.
• The method provides a unique solution for rotational parameters, overcoming common ambiguities.
• The extended Kalman filter approach ensures accurate state and parameter estimation, even under challenging conditions like occlusion.