A transmission model for motion estimation of instability space targets

Motion estimation is an effective way to rectify the distortion caused by motion existed in captured point clouds of space targets. However, the non-cooperative and motion complexity of instability space targets make it difficult to precisely estimate the motion parameters, especially in the linear measurement system with a single sensor. In order to solve this problem, we present a novel motion representation for motion estimation of instability space targets. The motion representation, called the transmission model , converts a nonlinear system of motion parameters into a polynomial system of orthogonal matrices, which improve the efficiency of motion estimation. Moreover, we exploit a self-constrained form to express the target orthogonal matrices, which makes them be further solved efficiently by transferring the constrained optimization problem into a self-constrained one. Additionally, an effective strategy is devised to solve the polynomial system of orthogonal matrices by progressively increasing the consecutive number of point clouds until the precision is attained. Experimental results have demonstrated that our approach achieves a high estimation accuracy and a good performance of reconstruction within few seconds under a variety of motion states in our research background. (c) 2021 Elsevier Ltd. All rights reserved.