Distributed Motion Estimation of Space Objects Using Dual Quaternions

This paper examines the motion estimation problem for space objects using multiple image sensors in a connected network. The objective is to increase the estimation precision of relative translational and rotational motions based on integrated dual quaternion representations and cooperation between connected sensors. The relative motion of space objects is rst formulated using dual elements to express its kinematics and dynamics. Two modular optimization approaches, namely dual decomposition and distributed Newton methods, for decomposing this cooperative estimation problem among the sensors is then proposed. Simulation results from single sensor estimation and two distributed estimation frameworks are provided and compared.