This paper proposes an autonomous algorithm to determine the relative pose between the chaser spacecraft and the uncooperative space target, which is essential in advanced space applications, e.g., on-orbit serving missions. The proposed method, named Congruent Tetrahedron Align (CTA) algorithm, uses the very sparse unorganized 3D point cloud acquired by a LIDAR sensor, and does not require any prior pose information. The core of the method is to determine the relative pose by looking for the congruent tetrahedron in scanning point cloud and model point cloud on the basis of its known model. The two-level index hash table is built for speeding up the search speed. In addition, the Iterative Closest Point (ICP) algorithm is used for pose tracking after CTA. In order to evaluate the method in arbitrary initial attitude, a simulated system is presented. Specifically, the performance of the proposed method to provide the initial pose needed for the tracking algorithm is demonstrated, as well as their robustness against noise. Finally, a field experiment is conducted and the results demonstrated the effectiveness of the proposed method.

To explore the lightweight structures with excellent vibration and acoustic properties, corrugated composite panels with different fiber reinforcements, i.e., carbon and glass fibers, were designed and fabricated using a modified vacuum-assisted resin infusion (VARI) process. The vibration and sound transmission loss (STL) of the corrugated composite panels were investigated via mode and sound insulation tests, respectively. Meanwhile, finite element models were proposed for the verification and in-depth parametric studies. For the vibration properties of the corrugated composite panels, the results indicated that the resin layer on the panel surface, despite the extremely low thickness, showed a significant effect on the low-order bend modes of the entire structure. In addition, the difference in the mode frequency between the panels consisting of different fiber types became more and more apparent with the increase of the frequency levels. For the sound insulation property of the panel, the initial frequency of the panel’s resonant sound transmission can be conveniently increased by increasing the layer thickness of surface resin, and the fraction of fiber reinforcements is the most predominant factor for the sound insulation property, which was significantly improved by increasing the thickness of the fiber cloth. This work can provide fundamental support for the comprehensive design of vibration and acoustics of the composite sandwiched panel.

Damage localization methods for composite materials are a popular research topic at present. The time-difference-blind localization method and beamforming localization method are often individually utilized in the localization of the acoustic emission sources of composite materials. Based on the performances of the two methods, a joint localization method for the acoustic emission sources of composite materials is proposed in this paper. Firstly, the performance of the time-difference-blind localization method and the beamforming localization method were analyzed. Then, with the advantages and disadvantages of these two methods in mind, a joint localization method was proposed. Finally, the performance of the joint localization method was verified using simulations and experiments. The results show that the joint localization method can reduce the localization time by half compared with the beamforming localization method. At the same time, compared with the time-difference-blind localization method, the localization accuracy can be improved.

This paper deals with the problem of relative pose determination between a model-known uncooperative space target and a chaser spacecraft using three-dimensional point cloud. A novel, reliable and real-time relative pose determination framework is proposed, which is composed of a region of interest–based initial pose acquisition method and a template matching iterative closest point algorithm for tracking pose. The initial pose is obtained by the principal component analysis method which aligns the region of interest extracted from the scanning point cloud with the region of interest of the known model point cloud, and a three-dimensional convex hull is constructed to extract the region of interest fast. To improve the iterative closest point, the registration between the template point cloud generated by the pose of last frame and the point cloud of the current frame is used to replace the registration between the local scanning point cloud and the global model point cloud. In addition, the performance (stability, low cost and their robustness against noise) of the proposed initial pose acquisition method and the accuracy and reliability of the pose tracking algorithm have been demonstrated by the numerical experiments. Finally, the effectiveness of the proposed method is verified by the field experiment.