Pose Estimation of Non-Cooperative Space Targets Based on Cross-Source Point Cloud Fusion

Jie Li,Yiqi Zhuang,Liang Zhao,Qi Peng

doi:10.3390/rs13214239

Abstract

On-orbit space technology is used for tasks such as the relative navigation of non-cooperative targets, rendezvous and docking, on-orbit assembly, and space debris removal. In particular, the pose estimation of space non-cooperative targets is a prerequisite for studying these applications. The capabilities of a single sensor are limited, making it difficult to achieve high accuracy in the measurement range. Against this backdrop, a non-cooperative target pose measurement system fused with multi-source sensors was designed in this study. First, a cross-source point cloud fusion algorithm was developed. This algorithm uses the unified and simplified expression of geometric elements in conformal geometry algebra, breaks the traditional point-to-point correspondence, and constructs matching relationships between points and spheres. Next, for the fused point cloud, we proposed a plane clustering-method-based CGA to eliminate point cloud diffusion and then reconstruct the 3D contour model. Finally, we used a twistor along with the Clohessy–Wiltshire equation to obtain the posture and other motion parameters of the non-cooperative target through the unscented Kalman filter. In both the numerical simulations and the semi-physical experiments, the proposed measurement system met the requirements for non-cooperative target measurement accuracy, and the estimation error of the angle of the rotating spindle was 30% lower than that of other, previously studied methods. The proposed cross-source point cloud fusion algorithm can achieve high registration accuracy for point clouds with different densities and small overlap rates.

Highlights

The pose measurement of non-cooperative targets in space is the key to spacecraft on-orbit service missions [1,2,3]
Estimate the attitudes of non-cooperative targets and of-freedom parameters and other motion parameters of the non-cooperative target, the algorithm we proposed in [37] is employed to obtain the point cloud contour model, using a twistor instead of a dual quaternion combined with the Clohessy–Wiltshire (CW) equation, and uses the unscented Kalman filter (UKF) to estimate the attitudes of noncooperative targets and improves the estimation accuracy of attitude angle
To verify the conformal geometry algebra (CGA)-based cross-source point cloud fusion algorithm proposed in this study, numerical simulation experiments and semi-physical experiments were conducted

Summary

Introduction

The pose measurement of non-cooperative targets in space is the key to spacecraft on-orbit service missions [1,2,3]. The service spacecraft approaches the target spacecraft from far and near, and the distance and effective measurement field of view (FOV) affect the accuracy of the entire measuring system. The non-cooperative target pose measurement is generally performed using noncontact methods such as image sensors [4,5,6] and LiDAR [7,8,9,10,11,12]. Because of the space lighting environment, it is difficult to achieve high accuracy via image-based measurement, and the measurement distance in this approach is limited. Most scholars use combinations of image sensors and laser algorithms to reconstruct three-dimensional models to achieve high-precision measurements.

Methods

Results

Discussion

Conclusion